{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/arya/.local/lib/python3.6/site-packages/sklearn/utils/deprecation.py:144: FutureWarning: The sklearn.ensemble.forest module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.ensemble. Anything that cannot be imported from sklearn.ensemble is now part of the private API.\n",
      "  warnings.warn(message, FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import GridSearchCV,StratifiedKFold,train_test_split,KFold\n",
    "from xgboost import XGBClassifier\n",
    "import lightgbm as lgb\n",
    "from rfpimp import *\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import f1_score,roc_auc_score,confusion_matrix,classification_report\n",
    "from collections import defaultdict\n",
    "from tqdm import tqdm\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "import seaborn as sns\n",
    "pd.set_option('display.max_rows',2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv('Train.csv')\n",
    "df_test = pd.read_csv('Test.csv')\n",
    "df_sub = pd.read_excel('Sample_Submission.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Freq_Of_Word_1</th>\n",
       "      <th>Freq_Of_Word_2</th>\n",
       "      <th>Freq_Of_Word_3</th>\n",
       "      <th>Freq_Of_Word_4</th>\n",
       "      <th>Freq_Of_Word_5</th>\n",
       "      <th>Freq_Of_Word_6</th>\n",
       "      <th>Freq_Of_Word_7</th>\n",
       "      <th>Freq_Of_Word_8</th>\n",
       "      <th>Freq_Of_Word_9</th>\n",
       "      <th>Freq_Of_Word_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Freq_Of_Word_45</th>\n",
       "      <th>Freq_Of_Word_46</th>\n",
       "      <th>Freq_Of_Word_47</th>\n",
       "      <th>Freq_Of_Word_48</th>\n",
       "      <th>Freq_Of_Word_49</th>\n",
       "      <th>Freq_Of_Word_50</th>\n",
       "      <th>TotalEmojiCharacters</th>\n",
       "      <th>LengthOFFirstParagraph</th>\n",
       "      <th>StylizedLetters</th>\n",
       "      <th>IsGoodNews</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
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       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "      <td>947.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.023323</td>\n",
       "      <td>0.039056</td>\n",
       "      <td>0.020516</td>\n",
       "      <td>0.013038</td>\n",
       "      <td>-0.018424</td>\n",
       "      <td>0.002831</td>\n",
       "      <td>-0.006407</td>\n",
       "      <td>0.008428</td>\n",
       "      <td>0.044759</td>\n",
       "      <td>0.005193</td>\n",
       "      <td>...</td>\n",
       "      <td>0.059328</td>\n",
       "      <td>-0.005919</td>\n",
       "      <td>-0.031999</td>\n",
       "      <td>-0.001397</td>\n",
       "      <td>0.033669</td>\n",
       "      <td>0.013292</td>\n",
       "      <td>-0.013279</td>\n",
       "      <td>-0.021817</td>\n",
       "      <td>0.018881</td>\n",
       "      <td>0.388596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.104679</td>\n",
       "      <td>1.085628</td>\n",
       "      <td>1.026794</td>\n",
       "      <td>1.345090</td>\n",
       "      <td>0.890268</td>\n",
       "      <td>0.970823</td>\n",
       "      <td>0.868676</td>\n",
       "      <td>1.136686</td>\n",
       "      <td>1.179691</td>\n",
       "      <td>1.129019</td>\n",
       "      <td>...</td>\n",
       "      <td>1.169027</td>\n",
       "      <td>0.959135</td>\n",
       "      <td>0.643179</td>\n",
       "      <td>0.821608</td>\n",
       "      <td>1.146482</td>\n",
       "      <td>0.860000</td>\n",
       "      <td>0.958807</td>\n",
       "      <td>0.513887</td>\n",
       "      <td>0.997459</td>\n",
       "      <td>0.487689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.453742</td>\n",
       "      <td>-0.107383</td>\n",
       "      <td>-0.219003</td>\n",
       "      <td>-0.427682</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.453742</td>\n",
       "      <td>-0.107383</td>\n",
       "      <td>-0.195476</td>\n",
       "      <td>-0.374323</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
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       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
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       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
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       "      <td>-0.230681</td>\n",
       "      <td>-0.081172</td>\n",
       "      <td>-0.164107</td>\n",
       "      <td>-0.277435</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>0.326735</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>0.107252</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.080193</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.018022</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>0.145162</td>\n",
       "      <td>-0.054961</td>\n",
       "      <td>-0.038632</td>\n",
       "      <td>-0.039427</td>\n",
       "      <td>1.000000</td>\n",
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       "      <th>max</th>\n",
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       "      <td>11.065546</td>\n",
       "      <td>9.184940</td>\n",
       "      <td>40.442907</td>\n",
       "      <td>8.479498</td>\n",
       "      <td>11.570173</td>\n",
       "      <td>6.461416</td>\n",
       "      <td>25.215295</td>\n",
       "      <td>18.826505</td>\n",
       "      <td>25.078049</td>\n",
       "      <td>...</td>\n",
       "      <td>18.446001</td>\n",
       "      <td>14.997385</td>\n",
       "      <td>13.943676</td>\n",
       "      <td>15.030734</td>\n",
       "      <td>15.146785</td>\n",
       "      <td>15.670854</td>\n",
       "      <td>28.750489</td>\n",
       "      <td>8.419193</td>\n",
       "      <td>12.437402</td>\n",
       "      <td>1.000000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 54 columns</p>\n",
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      ],
      "text/plain": [
       "       Freq_Of_Word_1  Freq_Of_Word_2  Freq_Of_Word_3  Freq_Of_Word_4  \\\n",
       "count      947.000000      947.000000      947.000000      947.000000   \n",
       "mean         0.023323        0.039056        0.020516        0.013038   \n",
       "std          1.104679        1.085628        1.026794        1.345090   \n",
       "min         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "25%         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "50%         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "75%         -0.351864       -0.318036        0.326735       -0.039223   \n",
       "max         13.771711       11.065546        9.184940       40.442907   \n",
       "\n",
       "       Freq_Of_Word_5  Freq_Of_Word_6  Freq_Of_Word_7  Freq_Of_Word_8  \\\n",
       "count      947.000000      947.000000      947.000000      947.000000   \n",
       "mean        -0.018424        0.002831       -0.006407        0.008428   \n",
       "std          0.890268        0.970823        0.868676        1.136686   \n",
       "min         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "25%         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "50%         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "75%          0.107252       -0.353977       -0.304257       -0.240708   \n",
       "max          8.479498       11.570173        6.461416       25.215295   \n",
       "\n",
       "       Freq_Of_Word_9  Freq_Of_Word_10  ...  Freq_Of_Word_45  Freq_Of_Word_46  \\\n",
       "count      947.000000       947.000000  ...       947.000000       947.000000   \n",
       "mean         0.044759         0.005193  ...         0.059328        -0.005919   \n",
       "std          1.179691         1.129019  ...         1.169027         0.959135   \n",
       "min         -0.318797        -0.352968  ...        -0.323019        -0.205212   \n",
       "25%         -0.318797        -0.352968  ...        -0.323019        -0.205212   \n",
       "50%         -0.318797        -0.352968  ...        -0.323019        -0.205212   \n",
       "75%         -0.318797        -0.080193  ...        -0.018022        -0.205212   \n",
       "max         18.826505        25.078049  ...        18.446001        14.997385   \n",
       "\n",
       "       Freq_Of_Word_47  Freq_Of_Word_48  Freq_Of_Word_49  Freq_Of_Word_50  \\\n",
       "count       947.000000       947.000000       947.000000       947.000000   \n",
       "mean         -0.031999        -0.001397         0.033669         0.013292   \n",
       "std           0.643179         0.821608         1.146482         0.860000   \n",
       "min          -0.079531        -0.118688        -0.151911        -0.453742   \n",
       "25%          -0.079531        -0.118688        -0.151911        -0.453742   \n",
       "50%          -0.079531        -0.118688        -0.151911        -0.230681   \n",
       "75%          -0.079531        -0.118688        -0.151911         0.145162   \n",
       "max          13.943676        15.030734        15.146785        15.670854   \n",
       "\n",
       "       TotalEmojiCharacters  LengthOFFirstParagraph  StylizedLetters  \\\n",
       "count            947.000000              947.000000       947.000000   \n",
       "mean              -0.013279               -0.021817         0.018881   \n",
       "std                0.958807                0.513887         0.997459   \n",
       "min               -0.107383               -0.219003        -0.427682   \n",
       "25%               -0.107383               -0.195476        -0.374323   \n",
       "50%               -0.081172               -0.164107        -0.277435   \n",
       "75%               -0.054961               -0.038632        -0.039427   \n",
       "max               28.750489                8.419193        12.437402   \n",
       "\n",
       "       IsGoodNews  \n",
       "count  947.000000  \n",
       "mean     0.388596  \n",
       "std      0.487689  \n",
       "min      0.000000  \n",
       "25%      0.000000  \n",
       "50%      0.000000  \n",
       "75%      1.000000  \n",
       "max      1.000000  \n",
       "\n",
       "[8 rows x 54 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <td>527.000000</td>\n",
       "      <td>527.000000</td>\n",
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       "      <td>527.000000</td>\n",
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       "      <td>527.000000</td>\n",
       "      <td>527.000000</td>\n",
       "      <td>527.000000</td>\n",
       "      <td>527.000000</td>\n",
       "      <td>527.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.034587</td>\n",
       "      <td>-0.015567</td>\n",
       "      <td>-0.011815</td>\n",
       "      <td>-0.034855</td>\n",
       "      <td>0.048186</td>\n",
       "      <td>0.004758</td>\n",
       "      <td>-0.039067</td>\n",
       "      <td>-0.042885</td>\n",
       "      <td>-0.023401</td>\n",
       "      <td>-0.022341</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004794</td>\n",
       "      <td>-0.046060</td>\n",
       "      <td>0.023906</td>\n",
       "      <td>0.068957</td>\n",
       "      <td>0.025588</td>\n",
       "      <td>-0.014241</td>\n",
       "      <td>-0.051894</td>\n",
       "      <td>0.029887</td>\n",
       "      <td>0.010378</td>\n",
       "      <td>-0.015275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.863755</td>\n",
       "      <td>0.991826</td>\n",
       "      <td>1.008872</td>\n",
       "      <td>0.060872</td>\n",
       "      <td>1.224778</td>\n",
       "      <td>1.193867</td>\n",
       "      <td>1.003432</td>\n",
       "      <td>0.636875</td>\n",
       "      <td>0.847441</td>\n",
       "      <td>0.766367</td>\n",
       "      <td>...</td>\n",
       "      <td>1.042504</td>\n",
       "      <td>0.927857</td>\n",
       "      <td>1.212529</td>\n",
       "      <td>1.285230</td>\n",
       "      <td>1.515122</td>\n",
       "      <td>0.874084</td>\n",
       "      <td>0.771676</td>\n",
       "      <td>1.241018</td>\n",
       "      <td>0.632055</td>\n",
       "      <td>0.697853</td>\n",
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       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.120401</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.453742</td>\n",
       "      <td>-0.107383</td>\n",
       "      <td>-0.219003</td>\n",
       "      <td>-0.427682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.120401</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.453742</td>\n",
       "      <td>-0.107383</td>\n",
       "      <td>-0.191555</td>\n",
       "      <td>-0.368707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.120401</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.258182</td>\n",
       "      <td>-0.081172</td>\n",
       "      <td>-0.156265</td>\n",
       "      <td>-0.274627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-0.335593</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>0.278956</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>0.143030</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.052216</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.120401</td>\n",
       "      <td>-0.247943</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>0.070299</td>\n",
       "      <td>-0.054961</td>\n",
       "      <td>-0.038632</td>\n",
       "      <td>0.004103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.662491</td>\n",
       "      <td>12.550362</td>\n",
       "      <td>7.082669</td>\n",
       "      <td>1.059753</td>\n",
       "      <td>13.846323</td>\n",
       "      <td>20.028000</td>\n",
       "      <td>12.122489</td>\n",
       "      <td>5.785330</td>\n",
       "      <td>5.614063</td>\n",
       "      <td>5.242416</td>\n",
       "      <td>...</td>\n",
       "      <td>20.662038</td>\n",
       "      <td>13.078061</td>\n",
       "      <td>18.783821</td>\n",
       "      <td>16.021188</td>\n",
       "      <td>31.707828</td>\n",
       "      <td>13.763001</td>\n",
       "      <td>12.596883</td>\n",
       "      <td>26.627430</td>\n",
       "      <td>7.783974</td>\n",
       "      <td>4.163982</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Freq_Of_Word_1  Freq_Of_Word_2  Freq_Of_Word_3  Freq_Of_Word_4  \\\n",
       "count      527.000000      527.000000      527.000000      527.000000   \n",
       "mean        -0.034587       -0.015567       -0.011815       -0.034855   \n",
       "std          0.863755        0.991826        1.008872        0.060872   \n",
       "min         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "25%         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "50%         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "75%         -0.335593       -0.318036        0.278956       -0.039223   \n",
       "max          8.662491       12.550362        7.082669        1.059753   \n",
       "\n",
       "       Freq_Of_Word_5  Freq_Of_Word_6  Freq_Of_Word_7  Freq_Of_Word_8  \\\n",
       "count      527.000000      527.000000      527.000000      527.000000   \n",
       "mean         0.048186        0.004758       -0.039067       -0.042885   \n",
       "std          1.224778        1.193867        1.003432        0.636875   \n",
       "min         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "25%         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "50%         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "75%          0.143030       -0.353977       -0.304257       -0.240708   \n",
       "max         13.846323       20.028000       12.122489        5.785330   \n",
       "\n",
       "       Freq_Of_Word_9  Freq_Of_Word_10  ...  Freq_Of_Word_44  Freq_Of_Word_45  \\\n",
       "count      527.000000       527.000000  ...       527.000000       527.000000   \n",
       "mean        -0.023401        -0.022341  ...         0.004794        -0.046060   \n",
       "std          0.847441         0.766367  ...         1.042504         0.927857   \n",
       "min         -0.318797        -0.352968  ...        -0.120401        -0.323019   \n",
       "25%         -0.318797        -0.352968  ...        -0.120401        -0.323019   \n",
       "50%         -0.318797        -0.352968  ...        -0.120401        -0.323019   \n",
       "75%         -0.318797        -0.052216  ...        -0.120401        -0.247943   \n",
       "max          5.614063         5.242416  ...        20.662038        13.078061   \n",
       "\n",
       "       Freq_Of_Word_46  Freq_Of_Word_47  Freq_Of_Word_48  Freq_Of_Word_49  \\\n",
       "count       527.000000       527.000000       527.000000       527.000000   \n",
       "mean          0.023906         0.068957         0.025588        -0.014241   \n",
       "std           1.212529         1.285230         1.515122         0.874084   \n",
       "min          -0.205212        -0.079531        -0.118688        -0.151911   \n",
       "25%          -0.205212        -0.079531        -0.118688        -0.151911   \n",
       "50%          -0.205212        -0.079531        -0.118688        -0.151911   \n",
       "75%          -0.205212        -0.079531        -0.118688        -0.151911   \n",
       "max          18.783821        16.021188        31.707828        13.763001   \n",
       "\n",
       "       Freq_Of_Word_50  TotalEmojiCharacters  LengthOFFirstParagraph  \\\n",
       "count       527.000000            527.000000              527.000000   \n",
       "mean         -0.051894              0.029887                0.010378   \n",
       "std           0.771676              1.241018                0.632055   \n",
       "min          -0.453742             -0.107383               -0.219003   \n",
       "25%          -0.453742             -0.107383               -0.191555   \n",
       "50%          -0.258182             -0.081172               -0.156265   \n",
       "75%           0.070299             -0.054961               -0.038632   \n",
       "max          12.596883             26.627430                7.783974   \n",
       "\n",
       "       StylizedLetters  \n",
       "count       527.000000  \n",
       "mean         -0.015275  \n",
       "std           0.697853  \n",
       "min          -0.427682  \n",
       "25%          -0.368707  \n",
       "50%          -0.274627  \n",
       "75%           0.004103  \n",
       "max           4.163982  \n",
       "\n",
       "[8 rows x 53 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_train.append(df_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Freq_Of_Word_1</th>\n",
       "      <th>Freq_Of_Word_2</th>\n",
       "      <th>Freq_Of_Word_3</th>\n",
       "      <th>Freq_Of_Word_4</th>\n",
       "      <th>Freq_Of_Word_5</th>\n",
       "      <th>Freq_Of_Word_6</th>\n",
       "      <th>Freq_Of_Word_7</th>\n",
       "      <th>Freq_Of_Word_8</th>\n",
       "      <th>Freq_Of_Word_9</th>\n",
       "      <th>Freq_Of_Word_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Freq_Of_Word_45</th>\n",
       "      <th>Freq_Of_Word_46</th>\n",
       "      <th>Freq_Of_Word_47</th>\n",
       "      <th>Freq_Of_Word_48</th>\n",
       "      <th>Freq_Of_Word_49</th>\n",
       "      <th>Freq_Of_Word_50</th>\n",
       "      <th>TotalEmojiCharacters</th>\n",
       "      <th>LengthOFFirstParagraph</th>\n",
       "      <th>StylizedLetters</th>\n",
       "      <th>IsGoodNews</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>1474.000000</td>\n",
       "      <td>947.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.002618</td>\n",
       "      <td>0.019527</td>\n",
       "      <td>0.008957</td>\n",
       "      <td>-0.004085</td>\n",
       "      <td>0.005391</td>\n",
       "      <td>0.003520</td>\n",
       "      <td>-0.018084</td>\n",
       "      <td>-0.009918</td>\n",
       "      <td>0.020390</td>\n",
       "      <td>-0.004651</td>\n",
       "      <td>...</td>\n",
       "      <td>0.021649</td>\n",
       "      <td>0.004744</td>\n",
       "      <td>0.004096</td>\n",
       "      <td>0.008251</td>\n",
       "      <td>0.016539</td>\n",
       "      <td>-0.010014</td>\n",
       "      <td>0.002154</td>\n",
       "      <td>-0.010306</td>\n",
       "      <td>0.006669</td>\n",
       "      <td>0.388596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.025138</td>\n",
       "      <td>1.053037</td>\n",
       "      <td>1.020198</td>\n",
       "      <td>1.078801</td>\n",
       "      <td>1.022597</td>\n",
       "      <td>1.055590</td>\n",
       "      <td>0.918922</td>\n",
       "      <td>0.987542</td>\n",
       "      <td>1.072980</td>\n",
       "      <td>1.014169</td>\n",
       "      <td>...</td>\n",
       "      <td>1.089801</td>\n",
       "      <td>1.056420</td>\n",
       "      <td>0.926215</td>\n",
       "      <td>1.119572</td>\n",
       "      <td>1.057124</td>\n",
       "      <td>0.829827</td>\n",
       "      <td>1.068085</td>\n",
       "      <td>0.559012</td>\n",
       "      <td>0.901743</td>\n",
       "      <td>0.487689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.453742</td>\n",
       "      <td>-0.107383</td>\n",
       "      <td>-0.219003</td>\n",
       "      <td>-0.427682</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.453742</td>\n",
       "      <td>-0.107383</td>\n",
       "      <td>-0.195476</td>\n",
       "      <td>-0.372919</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>-0.561952</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>-0.465210</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.352968</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.323019</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>-0.245959</td>\n",
       "      <td>-0.081172</td>\n",
       "      <td>-0.164107</td>\n",
       "      <td>-0.277435</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-0.351864</td>\n",
       "      <td>-0.318036</td>\n",
       "      <td>0.312401</td>\n",
       "      <td>-0.039223</td>\n",
       "      <td>0.121563</td>\n",
       "      <td>-0.353977</td>\n",
       "      <td>-0.304257</td>\n",
       "      <td>-0.240708</td>\n",
       "      <td>-0.318797</td>\n",
       "      <td>-0.073199</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.088406</td>\n",
       "      <td>-0.205212</td>\n",
       "      <td>-0.079531</td>\n",
       "      <td>-0.118688</td>\n",
       "      <td>-0.151911</td>\n",
       "      <td>0.119953</td>\n",
       "      <td>-0.054961</td>\n",
       "      <td>-0.038632</td>\n",
       "      <td>-0.021172</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>13.771711</td>\n",
       "      <td>12.550362</td>\n",
       "      <td>9.184940</td>\n",
       "      <td>40.442907</td>\n",
       "      <td>13.846323</td>\n",
       "      <td>20.028000</td>\n",
       "      <td>12.122489</td>\n",
       "      <td>25.215295</td>\n",
       "      <td>18.826505</td>\n",
       "      <td>25.078049</td>\n",
       "      <td>...</td>\n",
       "      <td>18.446001</td>\n",
       "      <td>18.783821</td>\n",
       "      <td>16.021188</td>\n",
       "      <td>31.707828</td>\n",
       "      <td>15.146785</td>\n",
       "      <td>15.670854</td>\n",
       "      <td>28.750489</td>\n",
       "      <td>8.419193</td>\n",
       "      <td>12.437402</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Freq_Of_Word_1  Freq_Of_Word_2  Freq_Of_Word_3  Freq_Of_Word_4  \\\n",
       "count     1474.000000     1474.000000     1474.000000     1474.000000   \n",
       "mean         0.002618        0.019527        0.008957       -0.004085   \n",
       "std          1.025138        1.053037        1.020198        1.078801   \n",
       "min         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "25%         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "50%         -0.351864       -0.318036       -0.561952       -0.039223   \n",
       "75%         -0.351864       -0.318036        0.312401       -0.039223   \n",
       "max         13.771711       12.550362        9.184940       40.442907   \n",
       "\n",
       "       Freq_Of_Word_5  Freq_Of_Word_6  Freq_Of_Word_7  Freq_Of_Word_8  \\\n",
       "count     1474.000000     1474.000000     1474.000000     1474.000000   \n",
       "mean         0.005391        0.003520       -0.018084       -0.009918   \n",
       "std          1.022597        1.055590        0.918922        0.987542   \n",
       "min         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "25%         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "50%         -0.465210       -0.353977       -0.304257       -0.240708   \n",
       "75%          0.121563       -0.353977       -0.304257       -0.240708   \n",
       "max         13.846323       20.028000       12.122489       25.215295   \n",
       "\n",
       "       Freq_Of_Word_9  Freq_Of_Word_10  ...  Freq_Of_Word_45  Freq_Of_Word_46  \\\n",
       "count     1474.000000      1474.000000  ...      1474.000000      1474.000000   \n",
       "mean         0.020390        -0.004651  ...         0.021649         0.004744   \n",
       "std          1.072980         1.014169  ...         1.089801         1.056420   \n",
       "min         -0.318797        -0.352968  ...        -0.323019        -0.205212   \n",
       "25%         -0.318797        -0.352968  ...        -0.323019        -0.205212   \n",
       "50%         -0.318797        -0.352968  ...        -0.323019        -0.205212   \n",
       "75%         -0.318797        -0.073199  ...        -0.088406        -0.205212   \n",
       "max         18.826505        25.078049  ...        18.446001        18.783821   \n",
       "\n",
       "       Freq_Of_Word_47  Freq_Of_Word_48  Freq_Of_Word_49  Freq_Of_Word_50  \\\n",
       "count      1474.000000      1474.000000      1474.000000      1474.000000   \n",
       "mean          0.004096         0.008251         0.016539        -0.010014   \n",
       "std           0.926215         1.119572         1.057124         0.829827   \n",
       "min          -0.079531        -0.118688        -0.151911        -0.453742   \n",
       "25%          -0.079531        -0.118688        -0.151911        -0.453742   \n",
       "50%          -0.079531        -0.118688        -0.151911        -0.245959   \n",
       "75%          -0.079531        -0.118688        -0.151911         0.119953   \n",
       "max          16.021188        31.707828        15.146785        15.670854   \n",
       "\n",
       "       TotalEmojiCharacters  LengthOFFirstParagraph  StylizedLetters  \\\n",
       "count           1474.000000             1474.000000      1474.000000   \n",
       "mean               0.002154               -0.010306         0.006669   \n",
       "std                1.068085                0.559012         0.901743   \n",
       "min               -0.107383               -0.219003        -0.427682   \n",
       "25%               -0.107383               -0.195476        -0.372919   \n",
       "50%               -0.081172               -0.164107        -0.277435   \n",
       "75%               -0.054961               -0.038632        -0.021172   \n",
       "max               28.750489                8.419193        12.437402   \n",
       "\n",
       "       IsGoodNews  \n",
       "count  947.000000  \n",
       "mean     0.388596  \n",
       "std      0.487689  \n",
       "min      0.000000  \n",
       "25%      0.000000  \n",
       "50%      0.000000  \n",
       "75%      1.000000  \n",
       "max      1.000000  \n",
       "\n",
       "[8 rows x 54 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test and train probably were together normalised then the splitting of test and train took place, this might give some unstable scores need to see individual features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols = ['Freq_Of_Word_1', 'Freq_Of_Word_2', 'Freq_Of_Word_3', 'Freq_Of_Word_4',\n",
    "       'Freq_Of_Word_5', 'Freq_Of_Word_6', 'Freq_Of_Word_7','IsGoodNews']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f2ab608ea58>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Xb5R0bQPKrcjdlc6E+tDtPxs/OPrnVS+Tu0/98N7hiR2oFD3feFY0yi2DQqDFCmP303/yO0rdeTaxiY5n5rpy9REa2TOm3lRCe9NZDfZ1qZY+zU7Kxe3qYJvLtu9Jj3/fUnSm7wVrNzb9sq7+zIiSGybn2eSGs9X/lm9LOqBpywWAuajcMVp/ZqRj2gBAKbQXgHiq+98O7v5xSedLGsk9znf3T9Rb7nQyoesvN/xk0sHRX274iTJhiU7NTHoiOeXt2BRNB1qsMHYX9xqxiVgIZBrLHaS8+aof6kO3/0xjmbC2nUgH5eJyHWzb97DtNUvDbmFQoyAsHXdBONbU5QLAXFTuGK1cLqbNi05BewGIp0adS90r6Tl3/7SkzWZ2SIPKLSsTesmDo2ypTs1kKrrEodDA8mg60GKFsbt1rxObiIXQVfIgpVTKLauDcnG7OtjmslQyoWWDPZOmLRvsUSqZaOpyM1Y67rLW1dTlAsBcVPYYrUwups2LTkF7AYinujs1zewjki6V9Ne5SV2Srq+33OkkA9M7XnWwHnrvy/TYX/2+Hnrvy/SOVx2sRKnLBnuHonu25JNU/h4uvUPNriYwRWHs/sHvzFe4ah2xiY4Xuuv4Q/eblHOPP3Q/haVu+VFOB+XidnWwzWWL+lK6es3K8e89f8n/or7mHtA+FyzU3j+9blLc7f3T67QzWNjU5QLAXFTuGG1nsLBj2gBAKbQXgHhqxD01T5N0hKQHJcndf2tm8xtQbkUL5gX6qyPCSTfy/atV6zU6r0Q/bRBEN6F+212Mtoe2K45drThZvuYOuSUUdHV3VGwykAry+rsDffTYQF0FOfejZ6zT3u4aYrWDcnG+g634nprN7mCby4LAtGLJfN120XEtzSk9qUCpeX3SyVdIXb3S2F6l5vWpJ9UZeRYAZpOyx2ipQJo/fRuAtifahfYCEE+N6NRMu7ubmUuSmfVNN4OZHahogKElklzSVblL16vWvW+Hkt/9O+m1n5B6BqXRESW/+3fqft0npZ6lU2cIgso3oQ7DaBALOj3RZKVi1771QY297pNKddCN0hlIBYV60jvUddPkm6d33XS2et5ypzRvcfX5c7pcPBMzyN/t6mCb64LAmjooUCnd+3Yo+Z2PSIefFR2kZPYp+Z2PlG8vAABmrHvfDiU3rC4abGW1ut9yZ5RzK7QBCtueQ/1d+j+vWaqBJX0yC2XuHKOhqdrSXqAPAqhbIzo1N5jZFyQNmNkFkv5M0tXTzJORdIm7P5g7q/MBM7vT3R+pdqGBhdLRb5fuuDjaaQ4sl065UoHVcoO3nDCUtj4yMSJf/nKIxYeRVNBwDY3dJmrXSMXoTEG4r8zN09PtzZ915O92dLCh9eKScwFgNqjYXphGvu051N+lL57Up0U/+sjU/M0xGpqk5e0F+iCAhqhrazEzk/RVSTdLukXSCkkfdvfPVJrP3Z929/zl6rskPSrpBbUsO/BwIuFI0fMdFyvwGQzysHd4Ipnky7rxrGg60GAJz5aM3YRnqi8kDKXdW6QdT0bPYdjwejKQCgplg9I3Tw+CoL35k/yNaTQk5wIAqlKuvZANigZbKdGWzbc9/+bVQ1r07+dFZ8wV52/28WiSmvoXGnEsRhsWaIi6ztTMXXb+dXd/iaQ7Z1KGmR2s6J6c99W28LDkfwHlM0gomXTpsjLT/0cRqFmYLR1v4TSdhYWXJ4QZ6VsflB7/WtP+q5cfSKWwY5OBVOauPclBBWesm7gEfWC5xs5Yp8ASU+O5f3Eurz7Z/EtpyN+YzkxzLgCgZs+nSrcXnk8NavzaiDJnqM1f8D/07+f/nl68KBHdpmn+UvbxaBkv07/gxf0LjTrDslQbtpVtaGCWaMTl5w+a2VHufn+tM5pZv6IzPN/j7s+VeP9CSRdK0vLlk//jZ0EiSiCFiWBgeTS9VslUybKULBgwIpuRdj8jZcekRJfUv1RKNOLrw2xUKXaVSEorTo7++5y7p6Z+fEPleCq18zzlSmnPFmnzxmj62+5q6L0KGUhl7qkUtwvmpbQt+7taeN63lfS0MpbSzmCBlmhkcv5ctlI68TLpmtfX1tCbaY6tJn9j1mt4zgVaoGLcAh2sUuzOn9etXQO/qwVv+Xr0T/ggqb1d+2n+vILbvZQ6Q+0/P6H5r/6AXvKNic5QnXMr+3g0VKXYDZLdJdsLQbLoVkXlzrCs9VisuA070zY0MMc1Yus4WtIPzezXZvZTM3vYzH463Uz/n703D4+jOtO+71PV3VJrl2V5ASECCYEhJqsTwvAmDgHGgAGz2QbvZg0OYTKTN5AQsjEJE2B44xBiwBDAlo1jHGMMGOMYSMg3HiCYQAIBDBMIslkk2ZYsa++uOt8fT5e6uruqtbXUKvn+XZcuqbfq0+q7Tj3nOc+ilApDHJprtNYPeT1Ha71Caz1Vaz21uro67QAGMHN5Mr2holZuq0F8pKJqmTDcx7pwrdwPyGK74VXgvtOB2z4tvxtelfsJ8SCbdnXxBOhp1wBbrwPunwFsvQ562jXQxRP8D+h18XzkKuDEbyZv53jX2t1IZfu1J2Hj0hPZJGiMk023hqHQ3G7h1BWv46ibX8WpK15Hc7sFKFMc7M78Oe1aYNPSgaXSDGWO7Wv+JgcFWe2FUAEw7dspcy6mfVvuJySPZNUtIaOYrNq1LZTtfwvq/jOgbvs01P1noGz/W6nR8V4Rap++CGpdakNCbPshMGslr/EkZ2Rdo0XHea/RouNSD5KrLKF0G3YwNjQhZPCRmkqpWq11PYDpg3itAvBrAK9rrf/foAYQ7wae+lGyg7S2ZTcw3iV1LQYSqm0YsgNy6ZPencfaPgQeXJA6wTy4AFiyBSivGdTwyUFMWyOUW08lE6DaG4HWciBS5K1dv4tntFL+HqZdazZSIQ5723twWV1a46i6Hfj9145F+Pm7knNxcbWkzji3O5uB7cuyG3pDmWP7mr8JiXUCz9ySqslnbgFO/1m+R0YIIWOPtg9T7dyWeqgHF0Av3gJU1Ej2kVLAxVuB9iaxEXbvEPsh3dbduRk442axB9j9nAw3bQ2Z2n3mZuD0m+S2o79cZQml27Dap1wOyy0QkpWh5F49DOCzWut3lVIbtNbnD+C1JwJYAOAVpdTLifuu01o/3t8DxIwCRD4xC5h0nFzkAGDr96CcGoNz1sjF0TD6d/EzDP9wcSvmPcFYsf4Ol5BelB1LOn1KJwGFFcC2Hya165Vm4Hfx7GyWNInpP5UL3kAd+oT0k564hbmfOwSXfa4Ypo7DUiHc/WI7DhhlGDf9p6K99iYgUiypM85Oc0UtcP49gBEC9r3jnVo+1Dk22/xNiDKAL30L6Nwrt0MFcnswmR2EEEKyomzva7qyY/7llJ6/S67jXrauEQZKA3KNd9e/pwM2cGRot2YqcPwVUOnp4NXHyO/0mpqDiSB227BtDaO/3AI1TkYhQ3FqunNQjxzIC7XW/532+gGjCyuhD/8i1MqzvGsMrpsnTqOt14mDc8KxfdfPSq/pVjwR6Noni3GvCcYM+x+LED/CxcCpPwE2Xp7U7jl3Zq+P6aQnuC+ec9aIc7TicGDV2UOvvcKLFMlCeaGBK4/tglo5C2iph1FRiytn10HHmlL1t+gx4MGFqdGaXfsB/Q/g3tPkObPrgIlTknOyGfaZYyNi4FGTZCgoE7B6gM3fSur03BVyPyGEkNxietclhFngX05pyRbZ8Ey3dWcuB7oPSKAK0D87NV/2bK6ax5D8kV5Ts2g88NQN3rUzB5sllE2ffus9p9N6vu1gapyMUobi1NQ+f48Ika4mCQd3p5M9f5fUGFw3P5ma21IvDs6Fj4jzx++Ec2q6OSHnzsL7lQ3i2Jy9Shbq7sdKJo3shyZjAzsG/M8vU7X77K+Ak64H6s7xTjNIT09wup9/4TLg0auHXqiaFynSB0XdezzTydS8Dan6O/CBODS/+gNZqJRMkBpBxdXAgoeB3/8kM7W8ZJLMqe75d85qSRu+71xqkgwNO5455/7PL5PpZIQQQnKHGQJO/gGwP2EbhArkthmS8mFemRlay+Olk4AZtwLhIpmrn/oR0NYIXPZ74MCHfdup+bRnc9U8huQPIyQ1t91rfnfQFJBcpw0mS8iKiz7XzfPWp996L1s2n8NIOPOpcTJKGYpT81NKqVZIxGU08TcSt7XWumzIo8uGUsDxV8ii2T3pFCbe1knNBeTxtgapV+h3wvnVdJu7Hlh+vNw3b4NEFLH7ORkS2lu77iLoXmkGzsWzrQG45wxxFpXX5Kb2Ci9SpA/80smg0oLu25vEiek4NB3nplvrT9+QmlpuhoCJU6CXbAGsGLQRhm0WIPTrr1KTZOj42Qvp2iWEEDJ0bEtsAXd0/MzlQGF537UIY53Amlmpx6uZKvf3x07Npz2bq+YxJH/Eu5IOTSAZSTz9RgmaAgafDm7Fgf27kg5N5/jp+kxf7/VHyyPlzKfGyShl0CrXWpta6zKtdanWOpT427k9vA5NQBoDOQsUIDnphKJyIs9aCbz5hDxWUSsXw2wnnF9NNyORnvbSauBXn5cdnPIaOjTJ4PHTrjJSa7I4qQYtu+S3bcvznQvKSdcDze8knaEOg7nY8iJF+sIpw+HGSRFfvFkiK2umSorZuCNFPyd+01vr065Nzq0JbGXijY4yfOnud3Dkz/6Cpn3N1CTJDX5zrrbzOy5CCBmL2LHMDs6blsr96d2e09NrzYik/85ZLbbFgoeB028BWt/rn02QT3vWcdi6GW31EEl2bJ9GPU75g8HWzrRtcWi2NfRfnwPRsp8zf7Bd0/3WoNQ4GaUE1zOnbe8TPVQguyl//C+JzOhoBr54pTSvCEf9j+dX081d+pMnLckFtrd2NTTUpU8mL5R+O26hCHDC1eI4am8E5j8EbPthMjVhzpqkU7S/aQi56uJHxiw6VAjlVYbjie8mtTdzeSJlrEVuOyVA3LTUA+M+JvUMm/8hv8NR7EcJLluV7K7+fpuNydQkyQV+9gKdmoQQknv8HEO21Xd67aLNwLRrUsvRzFwOQPvbqW57Vylxiu7cnPm84carHuJgm8eQ/GB6r4d02aFQ33x18GndnfvE5ohWAvPWA8/clExnd+tzsFrOhTPftiXCOt4p5SC80t6pcTJKCa5T0/BxQna1JMPDG16R9PFHvi71WC550v94JZNkV9Cpx+lcRGPtEn3U1siTluQGPwe6EU7tfueXPhOtAj55AbDyzKRWZ62UGjDtTUDZIfKagaQh8CJF+kDF2oEX7pE51TBFx09clzS2nEiMc+5Izqd+XRyVAu47LWWuLSuZhOqScK9T8yd/aMI9Z61E1aOL/DXJ5lakP/gsUmDSQU4IITknVODjgCyQv7Ol1+55I5m27ty3aSlw1m1SNsRdRuTCtUDhOKDlXTlWe5Nki0y7Rl7rdsiMhD2b7rClXRI8zHCmP2DOaiBUCJQMUkO2DbS+n1pHc+byZL1YdzBK+tptdp0coy8tDzU4xeu93bVE3Wnv1DgZhQTXqWmGZXG9v14ig2IdQHktUFCSfE5LPdCxJ7kTYmXZrTBDQNmh3sWpFz/Ok5bkDjMMzP0tsP9dl3YPl/sdsu24de5NXmyd+9cvEu2WTAKi4wZeU4iGGOkLZUjk+963ZKe5dJIYO25a6qU8R3mt7ErHOjKbrM1ZLbu/bm0+dwfMU36EdbMPxSuN1fjJH5rw0q5WXLe9ALcv2YawjqVo0rY19nd2o6z1LZjr5g5v/SASfIyQ95xrBNcEIoSQ0YsCLnxAGgc6c27pZKRkvwHetm64yNv+NcPAkz+UbLziarE1SiZlNl05+3bgmZuBM26WZnAjbc8OpnkMGT3Ylmx4ztsgG/BaA9qSiOLB0tGUWUdz01IpraAMoPww0Y1XQIvTWLMvLQ82OMUJDoh1Agfel1r4LfWZtUTdUZ/UOBmFBNuij3elFqGeXScOHQd3s6D+7FZ4Fad24MlLckm8M1O7qEw+7rPjFlNhqJ4uhLwMvsqPiP4NY3BpCLxIkWyYkcyUsHNXANuuT0mh0aEolGFAWzGo9j2y8Ji7Hug5IJ1LSyYCn74IOGGpzM9vPgEcNxtYcz4iLfX4XEUt7jlrJa7bXoBvnnoMzNJSwEguhGxbY2fDAcRbG3Dclrn5aQZAgkdfcy4hhJDcoJQ4h9Ln3PTmbF62bqzDO+Is1iG2xtbrxFlTeoi3s8hxxGgNVBw2/J+VjD26W4ENlya1e/49QGFF78O2rbG3vQc9cQuRkImq4ggMw6PxoOMw7OnwXpM5Dk2nT4ff2q0/Wh5IcIozLifdPH1T4Okb5FxrqZcgBoDln8ioJ7jhLPFu727lVrfcdkK7ty/r/24Fi9+SkcBPu/Hu5HM8CqnHZz+AqzbV4y8fdProtFCOse8dABq4+AkpnZDyHGqZDBIrnqnbjZcDp/xYblfUomXmSvyjqwjxeI/Ue916HbDiK8DmhUCbAAAgAElEQVQDs8Soq/+TRL9vvQ64f4b89mgmVPXoItw+sxZHTyzNMBT3tvfgslU7UBHxqZPIRkIknf7MuYQQQnKDFfNZo8VSn+dh6+4vPAwd59WlNhI6d4U4bL75qjhtxh8tUaB+zqLiatq7ZHBoK+nQBOT3hkvlfiQ31q/f+Bd8+H494vveRVfLB7AtK/U4Tjr3PacADa96r9vCRamNh4fqh3CCUyoOk99+Dk1nXO/t8N4UOPGbyffubB79JcncTY32vwe0fiA1+w+4GhyRMU9wIzXtuHezFTsO9e9vyOO2BVxwn0waTgRbNoZYV7DfOzfk4MZHu72pDVYcaPsQiJRI6QMjhJhWuGpTPba+1oTGA92ZtQbnrElEGl+QWq/l9FuALd9mTVgydPzm3LJD0XjZyygOK3R3x2C3NcIsKIJKL5HwyFXQizdD3T8j9f6OvZ7HDetYRoTm3vYedPTE8f0zj0W71Tbsza04p48R7LikVE2/UaIOOptlw3Mo6WSEEEK86cvOBVJsXb34cezv1vj7ng785JEm/OdpNTjGXQ5s2/Vixzp15Rv/Jimx02/0tgNKJg7K3g3cNZ91xXOPFfPWbsIhv7e9B8u2vYFbTylDSXs9oIuAvf+AbbUDVR9N/v/dZcC2L/OuB1ucptHh6m+Q3nzIOb5fM89oZbJfQ3G19CQpHqXa8qoF6q5XyrJUBw3BdWoaps+CtlC89e4Uydl1ibDxPgSdCN3WlzwJO96NuAqjI1yJcqjsr7Rt6PYmINaBcm3g7RYbP9/ehG+eeoxnpBE5yPHTrmGKkdfwaoZ+D5R+HFtfawIAvLSrFZc+AVx/6np8anIRQpECSU349amZ9Vpm3ApccP/AjR0aSiQdw/DuCGkWItT1AUrWL0JJSz0mOnUznbo8Di31UJZHak17U5/OSduy0LW/AfEDbdjTZuOhF1ux9KSPYf85q1D+8MLcGn/OeyZ2452O7DWVUdy9cCrn9CASKgRO/pHMiW6jN1SY75ERQsjYI5udC2TYuqqiFmWz6rD+NRsv7WpFsdED1HmUA4v3yBrP2TT1chbNWZOsUTgAAnfN93Lm0IEzdPrQbk/cwndPmoSS7ndTyisYM5cDRZVA8Xh5jTuVfPcOSemefiMwcQoQKfJeV6WnkCsFQAGt7wHhaP8CtNKx4sD+XclGWhWHJ8flRGGmf9aKWgmqGex7jiRePSQ2LU3WAmVZqoOGUazSPggXi7PSnZ4wuw7QtnfKQ9uH/TqsDYU32qKYtuJ/cfTP/oyzbv8fvP5BK/a1d8O2deYLrDjQ8i5U8zswGl5F5HffxTHGbtx8UimWbXsDe9uZCknSCBdLjcF564HFm+X33PVAuBj2gQ899Vth7UNNZbT3EC/tasW/PvY+msMTZaKOdXrvtoWL5G+/NAQv3KkJy6bI78bXGMJ/kKNDUWn6kzLnroKClYwaBsSZ2dYAzLxDnJtOCYSKWpkv01NrXl4ru8Hu47qdkwk9Fq2ajsn3fR6f2zYLN54YwvLf/y9et2rwyukPoecbf4W+5MmcGvNOmrvTjX13cycuW7WDc3oQ0Tbw3B1i5C7eLL+fu0PuJ4QQkluy2bm29rR1jfULcP006YvQ2KF90nWj0k/By1l01Q5xxEyckprS2xeJ1FW9fxfirQ2oLpGmnaP+mu/XELSjKb/jCjqhQm/tJjZBwyEDtSVIbpICSUdarENu27Y4JC/emrSDnXqwkaLsazLDEPu3az9w3+nAz48F7j8DaHwd2Pd2/9ZiTjp26weyflt1NnDvdHl/Ow4cPUOe52wKpNvfZTWSwl48fnQ7NAH/OqROLVCWpTpoCG6kZrwTeGWDTDSGKanmL60BPn+xf9h4y64+o868FrJXrH4R/zFzCiaVFyZ37Gxbuvu2vp9ZYPe5O1A+dTEu/1wteuKW5/uQgxg7BnTvTy2gfv49QLQCdrwHhod+lR3D3QunZuwgVxWF5MIFyIX3mZtSmrYg1jHwdNyBdk4nBwXK6gb2vC1Gnm3JvFv/gkTBO1qpmQp89QepURNn3w48fxfwlWtljk6PqvjKtcCfViQ7mpYdKj+uFB5jXWpDoKpHF+HyU9ejuqII0UgZQsURqCFEUnilnPXErd7rgMPu5k7O6YFEA8dfkalLeGxUEkIIGRpZ7NydDQdwVNjb1i00xGGz4sVW3D5rDcLrXeurC9eK7bHv76nRZY6zaMatwORPDcwJ44p2NFvqcVyiUeGlT0jwwKi+5g+mISjpG60lgtGt3XNXANFK2LZGW1cc1ablU17B8o6gdezgk64TH0Rf2XB+0YczbgUKS/3XYrYNdO4FejrF+a8M4A8/Sz3O+kXA/IeAhlfk3Hn+LmDhI4ARyk9m3lAzA30a6w6oUTQZEwTXqWlbwLO3yY+b4y/zFvfet6SzuXNhHH800N4gzk4zDJRMgq1MdMbingvZooiJy1btwMalJ6K6OCwT1oH3k5MekCywO/1GIFyEyRED4ZA5zP8IEjisHu8i1Is3o8s2UOKhX2WEcEx0P37/tWPRjDIow0RV1ITR+LdUp7q7jsjM5UDp5IGn49JQIl6ECoBJnwCa3pAI4FiH3DZdBoVH0x88chWwaLMYUMedDzxzc9KBWTIR2L8beGm1/ADA1S+nGjQ+epxcYiAcCaG6tGBIH8sv5WxiWQFqKqMp14OayiginNODh7a9dbl4c37HRQghY5Esdu7Pt+3C8rMne67VjFAEO7/zWZh2DNoMI37J0zCtLijH2dH6nmzen3Mn8PDXUm3fwdi7Hs6jqkcX4fpT1+P8utbRfc33c+bQgTM0rG5pgunW7sbLgcWbsbe9Bwvv/ROevPRjKPT635sRb4fkI1cBS7YApYfIfX2VDfBbh4WL/Nditi2RnAc+SC21c86d4u9wAl5a6oHuAzIerft2JA5nObJclFDwqkPqrIVHe4MjklNGeUxxFpQh4dNzVsvCZNGj8lsZcp87lHrmcrkIAiL4xp1A02sS1n3bp4H7TodueBUftrTj743tKWm+gCxkWzpjyR07Z8IKF3lPOsXVQKwDFaUlqCrmxYWkYft0bbYtRAsKYM9Zk6JfPbsOeH4F1LIpCN93Kqo730Z1kQmjdVdm17pNS6U51uLNwIR/AsYdOfCLz1C775GxiRVPRl7cP0N+d++XTaGZy0UjfkXH453AE98BPnwFOP1nkh5Wdoi8duWZwGfmA0ufB656UXaLLVczAR895mp+9Uszj9sady+c2ns96I2O5pwePLTPnMv0c0IIyT1+dq628fWTPoruzrak3QD01sI0lEZB0ysIPbQE4fv+BaH2BqiyQ5PpuqGIbNo/+QPgrNuAr/8JWPAwMP6o/tm78UTW3r535DeUjKtmanI9Of1GHFEVHf3XfI/O8XTg5IAs2q2MfYhfnHkI7n2pHfbs1Rn6BQDEu6VUk7v8Uku9OBANo39lA/zWYdmy7zqagOa3M9PiH/5aspu5c5xopThYs3VJd/4Xw1mOLBclFNx1SL/5KrDkCaDqY8D5v5YGR6wxe9AQ3EhNMwxM+zbw4EKp4Xbyj4CHr4RqqRdn58JHEhOICWy4OLlD8Zn5QM1npb6E6yRSDy5A+bzHcNtTu3HT+Z/EtRv+2hu1c9P5n8R/bd2Z3LFzdlD8CuwWjYcdrUJh+cTRWVya5Bcz5Kkb1fAqzK3XQc9dD/virVDxbsAwoVRI0g0A0epvLoJesgWqrcH7wgslFyo/+tp1G67ueyTYaMsz8kIt3iI7otNvBMq8oy/QfUDqZq5fJDvWjgFoRoATrgamnAc8MMtV6H81UP1Pos/CSnmuKyLZnvNAzuZXvzTzWNzG0RNLsXHpicHphEq8McI+hf/D+RsTIYSMVQxvOxcqBKNjL4q3zJK12/QbxcES6wBi7cDPv5RM1336hszSR277tO6cpH1aeYS/4yIek74KZhhw1/J0ejFMvwmY+E8p5Ukq56zG49/4Z5QUFuTump/riLf0pjJs6pkbfBoFKWUi9Isp+FxFLT5y1krc+VoUC+c+imhIwwCgtn4P2Lk5qd+X10o5pqdvEEe844x0fAgnfQ/45GzZXFUGoFwuGb/ow2zRyPGe7MFWic8xoEZaw12OLFeZgYbB8mgkwE5NKy4OzZZ6uSi6dyZ2JlIdFz4KfPhXmUwcTviG1CD0OIkKlIWXdrXgv7buxPfPPBYV0TAmlBXg39f9BU1t3ckdu47EDopf172icTAKK3hhId4oUy5O7vQAx4BrqYd6YBaw8BEox/HuGF4A8PufJmvE9qNrdAb9CfUfhYaSV81DOpdGGCvmE2Eck13g7cuAk3+Yqe2Zy2VH+OXVqQuYskOkHufxl0sRdLfRtG6+bEyVHSLF0dNS1o2yQwEzNylhkZDpm2ZuGGrI6e1kFKAMb10qXqMJISTnGB527szlgGHi0PKI3Odc6x2cciDuUl7r5qc6OAZqn8ZjQOPfxJE5d713I9nFmyX7xB3osm4+ypZsAYpqcvP/GK5O5XTm5B6lMtf2Z9+e6EQOoGQCquw9uORTH8Ob+2L4xMQo1P2ne5eie+QqqYNZekjSGRmKiCP98C8CK89KXecVlAGhcFLnlzwpmU7K7LsTeSgitrXXurDsEIliHOh6brjLkbGEAskhwXVq2q4Ftl/KIzTw8lroOWugnCgfI+TrDOrWskh+aVcLrqh7ETWVUTx4xQm4fe5nUh0p7h2Up2+QCWvcR4FIiSy66cwk2Yh3JSPbqo+RGoVP35BS7yQlCtMxvBY9Kk7NilpoIwz18lofp3qWiMr+7rrl0lAa4u60X83D3qZdZGTw2b1Gw6tSpP/s28XoeuI7SedlZ7No/V9+CnzkS8C262WTac6aXuNM23GJsHfTUi+bT0YouQjZuTn5nosfzx6NDPRbd1XFEe8mXKM15YwMHPec69bleffke2SEEDL28Jlz1Tl3oMLukow655oOpDb2AOSaH630dnAMxD5tc0VmGqZv6SfP+61Yvz9un7ABZ3DQtjTPcWv3+bukdJKrGWZBizSW0gse9taP45sY/3GgvDZpfxZVA/90RoYjXRzsLtvWMIDSAWijqBqoPDJzM2HOGqBksjhLB8pwOx2ZGUhySHCdmoYpF8VPXySORK/Oz4aJvV/4v1AlH8M4Z1cPkJDwNGeQnrMa+82q3oid6cdW4+dn1qDAboJtRmAWVScdKKMwko0ECCMMHPbPQNVRouNQWiRYRa043t049d++/gK0GYICoE+9AWrbD1KbrvSVUjDSTYBysDvtV/Nw49ITGUU3khhhSSHv2JNsFBStAp64JrkzPW+DOC23L5PozWglMO1aaRqw6esSfQn06tS2NWCEobyMpvYm0bTnIiSOdJxoXm1bqEQrQvF2qH1/l+tCW6Ov7gxDMc18rGOEgOK0xUHxRLmfEEJIbjHD3nPu/vdgPHo1YvM3IdzwSmZjD4cTrhY7YeEmcS5acSnd1AfpWT3j3ZumtuVThsQnVd7MYXkSNuAMDkYY+OKVHlHGYc9mmGrf3/27b1fUSpRlR1PST2AY/o50l21rWxbsjn0wrU5ZS4WjUNkCpwxD6spGKyT62LakxFPJxH6dO54Mt9Oxv/6U4WxWRMYMwbXoQ4XAtGtSa6OcuyIZCTR7FbQRxnXb4/jJuaacAB1NAJS8Li2dUZUdgklGBBuXnghtW6jq+DvMVdOBlnqYFbWIz34AmHgsDCflkSH/ZLAUlADHXZBaQ9ClXT1nNdQfbkp9TUUttBGCWjVTDLSKWujZq6HPvg0q1tn/SX6kQ/1zsDvtV/OwJ27lerQkG2aBGGebv5XU7Tl3Jh9vqRcdzV0vDsn07oslE6ABqPLDgM690PEedNkmNrzWhflzVkOtm5+a6vP8XcDpN/kvQlzYtsa7e9tgtzXiI6UaZvPbSWemX20uF0wzH+NEisW5/qBLY7NXy/2EEEJyS6jAY86tA164G2ipR3tMIzT3URQaNnpgQtsWip1SYSdcDX3c+VArz0x97cQp/s6ZeDd0WyOUHcd4w0Q8Uor/94f3cM2J5Ukb4tlfArNWAesXph63ZIL8Tq+1WTIph/8PptkGBqWA4vGySa+U9OfQlvztlRn6zE1SB97Lhp2zWhyV21cAn5qT3Fj3c6QbISAeg277EEoBoY59KcfVF66FyhYUYhgy9lwxEkFcfflThqt0AxlzBNepacUza6NsvFzqaO59E7q4Gqv/2o5vnnoMqopCqSfECVdLGLltyQRSMgkIhWEAqC4tQGz/hzDXzU05dujBuYgt2QajPIcXOXJw0tOWNPSApHYXbwaa3oBdPAnGtGugXLvYenYd1PN3p+4OPjgf9uItUH2l4bopqpaLouvioC9cCzVcof452J3OVvOQjCAxD90+/LVk3auKWuiQdApXXt0XZ9wKrUyg6Q2o31wE1VKPoopaXDhrDdqjh6J44SNSdqG9CXj+Luhp10AVlEoXyQfdi5BVGc6o/Z3dqGx7CxWbFmXWqfWrzUUOHmIdmdp9cD6wZAuAcXkdGiGEjDli3R5z7gLpWP7OH1FeYECtknqCoYpaxGevwT/O34yoYWFCsQnllZq7ZAtQ7lHjMt4NNL4O5XJKhmfX4dtfnoTn3tf44uw6eeyl1UDhuGQUm2v9h4lT5PhWTCI0SyYNPrrNC6bZBgdliKbSnNxaGVAVh2c6I9sagbJDRT92XDb/AWDqYmDzv8vjs1YBf1knNeRDiehJL0d6QSnQ9Jps8k+/UUo7udd9+ShZkO8gLpZuIP0kwE7Nbp86mraIPFSAsz49DiUFEeDAB6knxLO3Aa8/7HtCKJ9jK4sLYpIDfBuuWEDReJjxTujSSdCLHwfsOFSoUHYJj54O1H5BUnt37xBN2q6aP7YN3d4EO96NuAqjI1yJ8mhq50YbCu+ah6Pt9IdQEbHR0mOgxJyEw6GQdb9rsKH/OdidZs3DUYJte+u2+hgp/1F+GJQVk+6iXs+rPAKWWYjwgTeAc+6Q1JztyxBePw/hGbfKbve0a6EnHAt9+s1AySSotg+AF+6R6E/DlHPk2V8CX/q/Ulc5ocOiWDMKHIem835uZ6ZfbS5ycOA35+ayZhohhBDB9plzyw+VbKSt30sLHJmHgjmPo7ooLHZEX/O1bcsGaLxTnFAeDYCMxZtxXKWN1uKPozxhT6c4Mt2YIW+Haa5g2bLgEO/ybygFJWWU3J3OL1wrNeIB0aTVnVovE5Do4LnrgZZ3gYevTEYaOroMFco507E3GZnp1y9kqJvzQUvlZukG0k+C69R019R0Cvm+vFYuWJv/HaqtEeVzVgP2BKieA74nhG1r7O/sRlGsGSEdgxEqgDYLPB0x2vRfEI+67sxBm7QOJny1awJ//C9g52apMThnjez+te7OTM19+gZJVTfCUIA4NBtfg/rNRTATJRM6Z67EuyVH4fCqkl4t7m3vwYJ7X0iLetyVvT7lUEL/c7A7zZqHowQ/3Ta9IbvJ564AQlHfRmx2qBCh9g9T09fPvh145UGpA3TKjwErBtXeCJROhuraK42H3vmjRFh8Zj5wwjeAE/9N0oC2396bzhPSPosgx5kZ62BUxMFMtjmXEEJIbvGZc3WoECrWBbQ3SGqu89ibT2BSqANqX6M4KrPVuLRt6Wj+m0RG3VUv+gYKFBoazbbZd2PBkSDfEW+kf/jUu1St7wP3Tk823znjFul1YIal1nxnC9DyD6DyCNlQdwJQEq+HERKtuyMNKw4TPTe8CqybJxv+zns7NTlzVbLAikvjLKtH/v6fX4h9PdpTuVm6gfST4Do1Q4XAtG9npiWGCnsnEbVuvnQmL5no2WlPm2GgrQEV7Q0pTqPQ/I2wZj8A88G5vffFZz8AsyR1Qex2ZFq2xk82v4bfvdaY/+7MrD8xuglFfbQbTWq0pV4ucIseS+7aOfc/cpWk8hZPSNb86WhKppQnnlexaRF2nf4Q9hbW9jos+6xP6eUMH0rof452p1nzcBQQjmbWMZ61CthxT2oJBc9GbGuglIJaNy9Ty/M3AnXnJo85cznUhksSzX0egJ63AerPdcCU81Lr0DrpPCdeBSPkvRGFWEdic+CQ3m7r5CAk25xLCCEkt2Rbo3W1ACf/KLXu9vyNUM1vy6ZnyYQMG8KpcWnbGtaBRoR/4yoRZsd96hOaUIZiVg8ZGKaPE81p4Oqsz2bcCqyZJY8tegxoa8jctH/6BvFJOE757cuSx3AiDTua5Hgt9amOzO3LMm3p/pYL63VgJsopFE8Qv0C6/Q70fz2Xr2Aplm4g/SS4Tk2rJ3mxBBLh4QulpsWCh2URa5gyOW35DjD9J4C7RuGSrYDVA8OOy8LmiC9LNFBLPdTqc6EveRrdi38H047BNiMIlVQnmwRBHJo7Gw6kpMTedP4n0XSgBy/taslvd2bWnxjdWN3+2q2Zmuwa3dksxprHjqGuOgpW6aGw25pg2D0woZMdHl3Pq4jYKQ11stan9HOGF5YPLfSfu9Njg1hnZkrO+oWyI52YO6EUcPwVUiDdacRWVAVdUAaj+R1vHXXsST3mh38DLrivtzaR0jbwhUuAlWelPu+PtwCn3Qj0dEAVlGbWip2zBorOTAJkn3MJIYTklrjPnLv4caB0MtD8jjgvW+qTdkC4KHn76RvEhnCyLQrKoA98ANhxmM7xHHwaAGkzAhUdP3zBJfGYOI6ypbWT4KEMsUF/uyTTQemQKKmEOavF+WjHk05653GnBNLW68Qp/9d1wGcXJ+1bQNZR7vRqtyNz9w6pL7/wERlTqDB793MHKy6Rn24H5uLN3vb73PViv/e1nstnsBRLN5B+EmCnZpaaK3+6W1IeiquBovHAV68X5+bc9UCsA3bFR6D216cUle7dsUgszhv3NeOf73grGXVZrIH9u3t3PdrC43sdmoBEu1274a/4/pnH4oq6F/PbnZn1J0Y3Po5K2HHgqz9I3Z1euMk3Dcfc8zpCThTnvPWZzzt6BsaVFKIQe4C2AqCoOqU+ZXVJGDecMglHj48gjBag0/R2hi/ZwtB/4q/b6mPEsHt5LdDTKQ5NJ+XM6gHaGqCMEFBY4RkxD6snmYZWWCl1hZx6RE6ERunE1PeumSrOU8fRWVELNX8jcMmTcrxQRHazafQQQIx8vzmXEEJIbvGxF5Qdl4g2QJw3z94u6672JumY7tiau3dIltLRM6BP/xlUexNU8ztQidrbKTZpbwMgp26mCYSLoArKoULDtMyNxyQFPr3Ry4RP0LEZdJQCIiUSiRkukijHP9elBpy4Sy+dfbukoXvZGBOniC6VARw3G4AGWt8Xvb+8VrRcOjFV90/fIO9ddRRghqGKJ2ZqKlvUZNuHmQ5MP7+AYfZvPZfvYCkGx5B+kDenplLqNAC/AGACuEdr/bMBHcCn7iWsmCx23Y6hWSsBKwq8tAb6+MugYm1JhyaQuWNRUYsP2mx85rAyXP+VakwOHYBqfDvl4lU6uw7/58gK/ObFZMTb7uZOVERl4slrd2bWnxjdKNP7+1FmUreA/N56PTB7tXSRLJkgF8BxH4WKdwF/uCn53GduAmYuT+4UHj0D9rRrULzmzOR5MGc1jOIJOKbIxh+WHgej7UMY685zPb4muXPu0FIv42LoPzHC3rp1DLvZdVJg/dQfSxTGX9YCn7wQePhKiSJ2bx45Bdbn/VZul0wSQzJUIJH1KdEdiQLt7vc+8ZuZ58rqc5M1ighxY4Z80hODu69LyGA4uf62gb1ga1XmfdN/mpvBkLGL6WMvtL4nm5aJUjP48jViQ9T/STIy5j8k9sMzNwHFE6GnXZPshO6uw+22dytqgSnnAh37kh3Xe+vSD1O2hpfj6MEF4sCiDRJsrFiy1BEg9dw/f2lqKYW566WMwjl3SJkjP70bYXEcdrcCPe3A+kWpWn7mJuCEpalp5m2NYhOXHya2Szp9RU16BX35lWjQun/rOQZLkQCQF4teKWUC+BWAUwHsBvCCUuoRrfVr/T6IYSQvao6zp/IISSV//q40h+Ui6VY25Ty5OM5/KOuOxd6zVuL5dzQenHMowh2NUgNmTerFSz24AN+f9xh+8+IHvYeoqYyipTOW/+7MrD8xulEKOOdO4OGvpWoXSJZBcNi5GTj5+8CSx8VgS28Y1N4gO3u7dwBP/QhYsBFo3wNddiiM+8+Q5zop7bFOoPsAVPcBhOKd0oHPfZ64a8Q4VNQy9J8Ihpm5kHAWGNNvFIdmdJzouq0x2SHSSSHrbJaU8ZN/AJx4NVBxOAAlGvbTNZCIqLOkHpdjVBZXD87AYgO1gxNlyuamk+IY65AsDjo1CSEk9/jNuXYig62lXmyJRY8B5/1aHESuzAs9ZzVU8QSoe//FO6X3qR9JJpMVk3ncjACOzes817FpSw/JTJMdqi2QLeOKBBs7Lmszx3YtGg88dUPy+y6ZIHrubhVtA+IcPHeF1JZ3O9V7DiTKKrybrLcJpGoZSJZbKK4GymtEs3567Ctq0svB+tIaCTxIjywuLEvYQn1on8FSJADky6L/AoD/1Vq/DQBKqd8AmAmg/07NWJdc1Gb+CigoTd1B8VoUA8l6K7bl3d08VAgs3gKzsxtf+6wBY+v3xKl08VbPi1eRaffWJ6ypjOKO+Z/D5LICbFx6Yn67M9MJNbpRpjRdOW+FOMzd2p2zWpw9v09EQlTUShqEFfNuGDT9RrkfEEeSFQdeqoP6P/+edGimp7TPXA6UTvI2yMZ9NHluuJ3hDP0n8cScO/1GSTlvekMcmsfNTtWXU3uo+0Bm1PzZtwORYqlx2NYAtDf6G3qOrp0I/Bfukd1xp1ayl4Flx2Wx4jXXDUdNIDpJg4G2ZFPHXcT/nDtFV356ySXUCSHkYELb3nNueU3yOS31wP5d4iBKswPUuvnSH8HLTo1WAm2N0CqEuGkiFC6EsnwiycJFmWmyubAFDEb/j1lChZmNrNx+hZN/KFGXbm3PXC62reMIjXUAsXbgrtPEh+DUizdBi1cAACAASURBVHXjbNDHOpOp7e1NsgbMpsO+oiZLJmU6MI87Hxh3BDBvgwTW2JbUon3nj/1LIWewFAkA+bKqDwWwy3V7d+K+/mMY4sTp2p9ZjPqRq2SCcEh0wUPJBHEaAXLCV9QmH59dB2XHoe4/HRV3fRbGqrNlQV4zNTHJ1Ka+f0Utum0T3z/zWKy7/Iv4/pnH4pdPvQkN6dKcN4emg+OEqjhMfnMBNXqwLYkebt+Tqd1184HjLhDdVdTKzh+0aN3vgggkL7pP3QBMvQQ48IHc55Wmu2lp0inkxnGgXvok8M1X5fdIFIEmwcCMiA7XzU+mnH/8tEx9OfOvGfF+DFrqaz64ILuhByR3k//nFxLBvPx44PapwIaLJXLTPYeffbtEhnY0eY/fb3fb7/l94SyM7jkFWDZFfje+JveT0YW2JYLY/d0//DWoWOfgv//+Qp0QQg42tOU550K51kbOhqWfHaCUt50a6wDOuRPqie+IQ7N0YjKSLP25nc2ZWRy5sAUcx1HaOhIlk/p/DDI68Wv64/gVyg7JfHzTUol6XDdfyiusmZWMSm5vEs166bN4PFBQJvb0/TPkd3tTdvvAT+tO1KQZklqeS7YAV78svydOAbpagV99Xmzo5ccnG3z2J4XcHSzF9SEZpYxqNSqlLldK7VBK7WhqSrvYKEMWsX5piO5F8ZzV8vyTfyQTxvLjgVc2SNrD1S8Dix6VuherzvaexJxuZK6Ll55dhx/9fg+uqHsRc1Y8hyvqXsTvXmvMX3MgMqrIql0nbSVa6a3dtkbg3LskbcaMiNHn41hH6WTgX/8KnHWbRMft3CwOU21nPz+0LTuLboPswrXyfDrDD1qyz7mmONkramVOnLncX1/OTrXXY1ZMmvm01MuCw0vXZYcCV7+UnJvf+WPqc9oaJRJ0xq3A1/8ku+OO/v0MtFzXBMq1k5QMiexzru393XfvH/6aUNQJyUJW3RIyisk+51o+6dmJNZIT3WaY/nZA87uZduqc1dJQ8MkfADs3S4QmIBFjc9ZkbnRuX5aZJpsLWyAUlqZAix+XdeTix9kkKED0a43mxu1X8LMnbNf633GoA6LBaJWHltcA4WLgt4szyyZksw+cqMn09Zs7atIMSVT0uCPktxnq2xnaFwyWIqOcfMXJvwfAXUm5JnFfClrrFQBWAMDUqVN1xlGev0vqs3mlAJROBr7xItDeBF08AQpKdv3m/VYuoq3vA098Fzjpe3I7EvVfnO/eATx/F/TizbCtOLpsEz3RCfjvt5/tbSY0oUihpcdAUYQnOelDu07aimPIpWvX6QIZ75ZO0GZYiqi7C0lX1EqkWuc+oLAcqKyVlIinfix6NSPA774n6T5+xdpLJ6d0i2ZKJMmq23gnsO36ZPr5gQ9EQ176inXIbrZfYXIzLCk5sU7ggvuTRp2j61ABcI+rJmy69s++HXjuTuCLV8oOuVNqJJuBluuaQCycPqrIql2/RkFei+lcQ52QLPRp5xIySumXneuVnv2NF2WT1I7L7fIaYO6DwAOzM8vYALJ5WfkR2eD8x38Df75fAk6KqxOptIkSImWHSOOWkonSbOjpG2QDdM6aVIdPrmyBUJhNgQLKoLRbdijwb3+TUkx+azfn75nLpVwTIPbp/3erNFhb8LAEWZkR4PFvA1/6t4HbB4MtMccUcjLGyZcH4wUARymljlBKRQBcCOCRAR0hVAR85VpJt02LosTM5ZKeWHcuEIrCChdJLYyHrwR+9QW5Hwr40rckXPyBWUDD3/xTFypqEfvytfjutj346C2v4xO3vooeC6i7+PO474xifG7bLBy28gs4bst5qDjwv0wrI9kJR6Wj+ctrM7V79u3iwNRaoorvnS4pCVPOA956UhxKF2+VAunKlPT12z4DrDoHgAJOuxk4eoYYdW2Nku7jRNc57zFnjTilxh0JlE6UCzUgjs62BuqXeGOEUtPPN30d+OPN0tE8PZJi0qckkjJ9Z3r2aqCnTRoC3DsdePRqMRDPWwF8489i8L1wj7zWOTcSm0qYvxH4xkvQizdDV30M+vSboR2dO8fPZqD1Z3d7IAx115uMHAWlHqmCq6CrPj78Bj11Qgg52Cgo807PjnUCv/uBOFVWnwfc9mlg1Uygs0XSZL/x52TmhdMEc80saCMMmIXAzi1SJ96xj+87HWh4VerJR8dJaZttP5SggH/5qTQsTE+TzbUtQMYW4ah3eaMt10rDVtvyXldVHi7rs7Nuk5IKbtv0K9eKIzNUKF3NSycDJ13nH6Xcl30wmKhJppCTMY7SOj8bw0qpMwAsA2ACuFdr/dNsz586daresWNH7229fzfUc3cBn5knExC07Prtext45qbUyJ1FjwErz8zcVZlxK1DxEakx4dVQZc4aWCWT0NXVibauHuxutfCTPzShqS2GjUtPxHi0QD32b8CnL0p29315LXDWz9lUZWwxpAKpWbUbSXTO62wBWt4V/Zz6YzH20vW66DGpU9T8rtz36NXemq46Si6aHXvEgAwVyuu0LRFw7h294WieQkYLOdWtvf99GHvfkjmyZAJw6k+k0+MRXwb++V8lGs62gBdXAZ9bKBoumZAsgB7rEGf6/TM8tP2odEZ/abXcnrcB2HQlMO1a6HEfFWPQCEGFCiTK3tHr0TNk99sI9W+3OpcNW3juDCe5nXNbdkFtuTbjWq1PvxmqoibLkXIAdXKwMWjtpus2nefu+NpgDz1ovnhkVead07Oa6ySY5N7Offd5oPbzYhcYJmAWAL8+RZyWW6/ztl8rjwRWn5v52JItstkPiHNp5+bUxxc+AlQcLrf7c41n87axRI7thd1QW66RTNCuFonA3L5M/AqOvdrZLE50bUkEcfM/JDLT8SOUTACmXSvNV80CIFwoz3drzLYl2671fUk5p31wMJLnBixji7y1adNaPw7g8UEfwIoBz94mPw6LN0txXjct9TLp+HXFM0zgqhflomZbwPyHoI0QVKQIiFbBaHoDxb+5CMUt9ZhYUYv7Zq5Ec8lRqCqOQLXZ3t19GelGspGu3Zqp4viZOEUWC05hczct9ZIm3vwOUDS+D02HxMFU2o+C5X713vrTDY8cXGhbIiad7o52TBYSre8Be3YmjT5AnJot9cnmVw5Xv+St2wMfJh2as+uAonGSlh6KQLkXG20NqXrduRloeKX/enV2t3PBYFOAyMhjx0Ur7oUwMDLOGeqEEHKwYcWBhy5Ove/SJ7PXkw8nNvnnrpcMusS6Ss+ug3r8Gpm/nXWW04naeW1bgwQJlEwceVuAjC3smGjthKWyCe+mpV6CUMLFsg5TJvCXtcDvE7bE83eJL8K2JOCqeIL/td4wpFFQdBztA0JyQN6cmkPGCAHffhuItSfrsijTv4aLX923xtdkx9Cpf5Gov2KFi2G0N0EdeF9qtHQ2A9uXoWLTIpQv2QK0tkBDQ7kX+Z3NMqGdcQvseBxo+xAqXADEunrHqEsmweijkLRta+xt70FP3EIkZKIyGkZzZ6z3dlVxZFDd1Z3jattCJVoR0jGoAUyg6eMa7DhyRS7Gk5fPZISAb70FWEldwCyU263vAaU+tQiVEqOvaLzs7Xg9p/wwaKWAlnroUBTaisOGQkeoDGX2AcDqhrJteU/DhI53QZ13tzhMldGrc8Q6xSjt3Ju80EarUm7bhVWw2vdAWd3QZgHM4vEwuvZCx3sQV2F0hMpQGtsHZcegzDBQPBHo2gcd75Hzy+qBsnsA24JKXPxtKOxt74Ft27A0oLXu/V4AeH5XufwO86Vxv/cd6P3DOkZlwDj3bqBrb1K3hVXJBmufmQ+c/atk1ORA5uKyGqlVpDV0uAjobgWMECyjEGbrbtG9FQPsGNSCTUB7o9SMBYB/+Sl0T6IpkRGGZUSgbQtGvAuWEUZnpALR+AGE7S7AtmGZhdiHMoRCJiqiyf+bbWvsae9GV8yCqRSikdTH3d9Va1cP2rstxG2NsFmGCSUFMAx/7fp9ZwCyzslZv2e/SBNGoGSSrb7biLw/F9BjAp5bhPQPM8saza+efKwDaH4biI6DXvw4rHgMZigsUfbOhpTTxHXmr8RxVF4jGUhmBDreDez7h7xXpAhWrAewemAbYcAwYca7YIQLoIrTztt4DLpjjzizbAswI7BhwDCMzOcCYhu3NYjd7ESgFlXJZ+6D0baOcg1sVM5teVujZdNptBLYsxN64icBuwfquAuAT88HrG5ILLGCChXKmi35QSTiM94p50E4CruwEvu7YiiKNSOkYzBCBdCFVbAONCJkdQGGgbhRiDazDOWFYRgde1Jej8IKoFPWXJZZCMPqhrJjktUUKZbHne/QigNdzbK2sy2pa59YkyHeI8ez41IOyjl+dJy8tnOfvE5bQCiabJiUrhdtA20fymNaJ5y+staE1d37Wmedl/U7tcSHAivRV6JkUr/OrxRS/ueGRNSa4cyI2eEgF+MnAya4/+HCccC+t4AHFySjJOeuB+Y8AKybm7xv5nJJR5+5XBpKuO8PFwFPXCP3bVoqzsl186HWzYO56DE5kTd/K6NwtYp3A7/7PjDt256RmhoaqvFVqHefAw7/YuoYZ9fBnvAJX8embWvsbDiAy1btwO7mTtRURnHn/M/htqfexO9ea0RNZRR3L5yKoyeWDmhid467bNsbuPHEEMKPLhpQqLvXuAYzjlyRi/Hk7TN5aXd2HTDuKNkVPOLLUs/lwYWpet14hTjdZ62UCTpd0+fcCTzxXajjrwCevwtq2rcBswDm239E2UdPgmpvzDgHlOPIP3eFNIFpa5TjdjbLbqQzxqNnANOuSbmtpl2DsOsz6Nl1wDM3Q+3cjPDRM1A27Rqo9M/4ygaorn0InfANudi4xqMvfADvmh/Bf255A4v++Qhcu+Gvvd/Lqou/gO64nfFdHVVdgrea2nLyHeZLD37v6/fZcvmZB4JRUO6t269tB565Req+OtEVR8+Qx9KfG+sUrW28PFXb7Y1iSP7hZ1BfvLJ3gyk0uw5o3wuUH5qhF8xZIwbYhkugXMcKFVcD0MAjV8EsnojwyT+Acr02VFGL8gvW4E1dg5bCGD5SVQwAGd/BLRd8EhPLCvGRquIUx+d7LR1o7ohh6Zo/9z73/iWfRyyu8fMnd2Zo1+87czTtNyfb1f+EnY3t3t8ztHdKc/UxUu+Uqc6pFI7z1mPhuHyPjAQFlhEgpP8UVPqv0f7wn5nN/9xrslN+DBXvROjhK8WuTY+wL5kgNTvd9umXvw213mUzz16F0DO3JKM7XYEr+sK1UM55G49B7/t7io2AilqY590NbL8N+qTrks8FxFnR+DfJQHGPvWRCItXYf1k92tZRroGNyrktr2u0xHrGU6eGATxzE9S5K4C6c+S7P/lHwKalSVv07NslyOmk67ztspnLYZfXInRgHwo2LkyxS8LP3Nyr2/DM5SgsqYFubcv0bRRXA0/dANXegFDi/VMabkbbxOmvbWD/Lkmld9aV7jWdu5yU+/ilk6X0U8u7qceev1Fs7xS9PCBOw6duyPSLpJ1775qHY8G9L/h/p1Zc6uSm22sTp/TfMeil6ZnLgUixrG3HHTl82s7F+MmgyFtNzYHiWSPr/jMyd1Au/h3w3g5g/MflRHTqa9ZMTdS3+BgALU6hhy5Npi8AEjLuhJp/488yWXnVfAGkCHXVUclFvPs5znEWPSoNMdIe14sfh/LpmNd0oBvnLt+O3c2dvffVVEbx/TOPxRV1L/be3rj0RFSXFvT7/+cc9xdnHoLPbfMYcx/pm37jGug4ckUuxjOAY+S+vpuXdhdvBpYdJ41WXl4r9d/SdQwA89aLsz29XmGoUPRWUZusWTRvg+yi7Xkz6aB3v2fCkZ/x9/yNqXWN5qxOrYGUfjv9eH6Pz10vf++v9xzPK6c/hPfjpfiPx15L+V7uW/x5fH/Tqxnf1YNXnIDZdz2bE13mS+N+7+v32QbwmUdIt48D0Jm1Mo+eAZz2n9IlvbBCdokfulwiLOJdsoBxIoPbGmVujXeLbtxaXLxZDMJ0vTjngV+t5D075b5Qga/W9uhyTDm0HAA8v4P/mDkFUw4t7/2/Nh3oxv7OGBbf9ydPfX7/zGMztOv3nTmv8ZuTY0u24aQ7M4+1cemJqFYtwD2neNcdu+/0Ac/vo5Aca7ce6vm7pY6xYUqkwktroI+/DCq9SD8hXrQ1eJ9zmecWa2qSIDIy9sLFv5PrebQCiJTI/Y7j5KkfJ22BcUcCja97X7/Tr/192aPpt93nbcsuoOl1f/t463Wp5/j+3d7X2Bm3ihOw3L9G82hbR/XS/7ltRMnfGq0east3ZA1WXiMRhrEOSRX/7RJpQNXdKk9eMyu7/rZe52+XzdsArDm/b936Pc+xmQHv95+3AYiWS7RgT0fqMdxj9hu/Y0unv3c229ux4bOsNV85/SGcdd+bvQ9nfKd+59iSLVnPrxT8NO34cCZ/avi0PbDxj4Iw7bFDcF3Gdty7Jku8S06c9PqaiQ56vQ7Hi7emOjSdUHPnb7/jVx4hHaVP+THQc8D7OXai3qG2fR6P+36snriVMoEDwO7mTlREwym3e+KW7zGyHXdCkfL5v/X06/Xp4xroOHJFLsaTt8/kpy078b7RymT9N686seEieNYrXOxKz3FqFiklOnRek/6e0Urvv6FTn59eA8mvJpJzDL/HDTP1M6Q9XhGx0REOZ3wvRRHT87uKW3bOvsN86cHvff0+Wy4/84Dw1W3ce67buVmaXt07PVWbysjUNCCacHTh1qJteevFT9PhItG9cwzn/rTnVURsdGiz9//m9T8tipgp/9eeuAVDZT7X0WdFNFO7ft+Z8xq/OVlZPf7fs+rx/uxWbFDz+5jHtjJrcAPA5y/Oz3hI8Ij7nHMH+7lFiBfZ1mh15yTvcxwNa2YlMjBWy3zd+r5cw5/8YUa0nB73UYmIc+jLHk2/7T5v7Xh2+zj9HPe7xjolcrIw2tZRvYzSuS1/azTLuwb31S+L0729SRzYGy+X+7PpL5tdpnzW4+m69XueYzM7t72OH+8Rjacfwz3mbDVuvd47m+3dj7VmRcROeTjjO/X7f/VxfqXgp2nn/zWc2s7F+MmgMPI9gEHj1LxwU1GbdJo4tTDSH3fuL5mQfNwJS96+LBm23d7k/fr9u2VS62yW5hZez1FG6u+MMfr7kiMhEzWV0ZT7aiqjaOmMpdyOhEzfY2Q7bmOH9h5TKNKv16ePa6DjyBW5GE/ePtNAtOul41iHv7bdf1fUSl0TZfT/Nc7ftpX6/PRxZDu/sj1uW/LjM56WHgMtnbGM76Wjx/L8rkKmkbPvMF968Htfv8+Wy888ILLp1jD9v29HF8537qeNWEfyMbcWDdNbL36ajnWI7jubU9837XktPQY6eqSmj9934DzuEAmZsDV89emlXb/vzHmN35yszYj/9+zULE3/7GZ4UPP7mMdXu8Hd1yUjjN85d7CfW4R4kc1ecK+9zrlTsowWbxbnpuP8eOrHcv1uawSevkEivRLP6ULada4vezT9tvu8NULZ7eP0c9zvGhvrkMeyMNrWUb2M0rltVK7Rzr5dMunMAtEm0Le/wU8z2mc9nq5bv+c5NrPf+2st36EZzjxGX+tMty09ENu7r3MxYXu7yfhO/f5ffZxfKfhpOtaRyGwcRm3nYvxkUATWqWkVVksNP9fFUc+ugy6skvu2LxNHpfvi6UxGs+ugzQiwcBNw2e8l1bbyI9Dn3QNr0WbglYck3Nzr9X+6G5i1So7j9R4zl0MbERnbG09IHYX0MZb4d6WuKo7g7oVTeydyp6bmhhd39d6+e+HU3iYT/cU57ooXW7H3rJWpY75wrRT57cfr3eMazDhyRS7Gk6/PNCDtemmsaLwYgn5O+V6dr5IdujeegC4/3FOrva85d0Xq619ak6rdxHnjvu31GfDyWt/HMbtOjvvsL4Hy2ozx6AsfQMm4Sdjw4i7cdP4nU76Xw6uKPL+rCSUFOfsO86UHv/f1+2y5/MwDwUu3UpewCvjTrzMfm7VKvm9HjxWHQ89ZI3+ffXumFksmyWMpG0x1QNNbnnpB6WTg/F9nHqe8VgqUb18mOvR4bfcFa4CiKhxeVYSq4ojnd3DLBZ/sfdyhqjiCgpDC8nmfTXnuYeOiuHvBVE/t+n1njqb95mSzpNr/ey6qlnk7fR4vmeR9fx/z+1jHb861Cg/u/wsZAH7n3EF+bhHiRVY7d8atktq8YCPw7K+kbNLDV8Iunoh/HAAOICoOI8f+bWuUrKSHr0S8eDI+tMpx4NxVqfbprFVptsmqpD2aZu9q93lbMsnTRsB5d4v9kH6Ol0ySaNJ0u6PicHksC6NtHdXLKJ3bRtMardfWff4uqUVpRkRjffkb/OyymcsRNwtSdZy+jko8rxNhWHMe8LZ1/XwRs1fJZkFRdaJJTTg5XiB1Tbd9mawB049feaQcI/3YlUd66OWB5Hi87HvXuVcyblL277RkUobvBLPr+jy/UvDS9Mzlsn6uPHJ4tZ2L8ZNBEdiamgAQ7+qC2dXU21nPKqzGnq5kF1nDDMvi1o5LtJoyAA1Y4SharEKUox2hREfcmFGAtnAlLEujzG5BSAGGUoDdA9g2tBGCViYMbcE2IzCsbsC2oEOFsLWGaXUDhildnKPjYNs2u58PMyPY/Tyn9VoAb+3u7bYxDvul612oMBHVGIMORUVjdneyk5y2kt3ljIikCDgdzBMp577dz7Xdexwd75KukcoErB4ow4BSpughrdu5f/fzHmgzwu7nQ2CYup8Pu25ROA5Wx15YRhhdoTKUxpt7uy/CDEu6hUuPbaoYRfH9MGFLyrq2RLNmJFmWQ5mSomaEYEXKYPbsT+l+DtuCHSqEgoLSFmRSjyUiRr26n1ciGm9FyO6C6lf3cxumwgC6nxvsfp57RmTODRUWDmmQ5CCjf+fWmKqp6cVTtVcP27G/N+PYYTs2ycqIzLmtMRsV1j4oOy71Mm1Zo8XNQjSjDJ1xjaKQQrneD1PHYJtRaDsOw47BTlzPu2IaChoVej/CultsBjMsNrBj33p1P7e6YITY/dxnYKPSbhhNtq7qaEx2slaGNN7paYe240CoEFrbsp5xr6Pcdll/up9HZV3F7ucHTffzUXDyjx0C7dQkZITI+QWTkBGAuiVBhdolQWXMOzVzgZ9jlE7NvME5lwQVapcEFTo1cwgLShFCCCGEEEJGhJPrb/N+YKtHt3U/2IWdEEIIIaBTkxBCCCGEEJJnnnt7b/+fnIPI1adqr2Z0KCGEEBJwApN+rpRqAvBuP58+HsCeYRzOSMLPkn/2aK1PG+yLD2LtDpSD+bMDuf/8I6lbL0bj98kx9Y98j2k4tZvvz5YOx+PPaBoL0L/xDFq7Q5xzR8P/Kt9j4PsP/v1H2l7I9/9qpDnYPi8wcp85H7ZukL5PjnV4yMVYh6RdkkpgnJoDQSm1Q2s9Nd/jyAX8LAcXB/P/6GD+7MDY+/yj8fNwTP1jNI4pV4y2z8bx+DOaxgKMvvG4GQ1jy/cY+P7510B/CdJYc8HB9nmBsf2Zg/TZONbhIUhjPVjIf2szQgghhBBCCCGEEEIIGQB0ahJCCCGEEEIIIYQQQgLFWHVqrsj3AHIIP8vBxcH8PzqYPzsw9j7/aPw8HFP/GI1jyhWj7bNxPP6MprEAo288bkbD2PI9Br5/cAjSWHPBwfZ5gbH9mYP02TjW4SFIYz0oGJM1NQkhhBBCCCGEEEIIIWOXsRqpSQghhBBCCCGEEEIIGaPQqUkIIYQQQgghhBBCCAkUdGoSQgghhBBCCCGEEEICxbA6NZVS9yqlGpVSr7ruu0Up9YZS6q9KqY1KqYrhHAMhhBBCCCGEEEIIIWRsMdyRmvcDOC3tvm0ApmitPwngTQDf7c+BTjvtNA2AP/zJx8+QoHb5k6efIUHd8iePP0OC2uVPHn8GDXXLnzz+DAlqlz95/BkS1C5/8vhDcsiwOjW11n8EsC/tvt9preOJm88BqOnPsfbs2ZPj0REyMlC7JIhQtySoULskiFC3JKhQuySoULuEjA3yXVPzYgBb/B5USl2ulNqhlNrR1NQ0gsMiZGhQuySIULckqFC7JIhQtySoULskqFC7hIw98ubUVEp9D0AcwBq/52itV2itp2qtp1ZXV4/c4AgZItQuCSLULQkq1C4JItQtCSrULgkq1C4hY49QPt5UKbUYwJkATtZas6YAIYQQQgghhBBCCCGk34y4U1MpdRqAawBM01p3DOVYtq2xt70HPXELkZCJquIIDEPlZqCEDCPULgki1C0JKtQuCSrULiGEjByccwkJHsPq1FRKrQXwFQDjlVK7AfwQ0u28AMA2pRQAPKe1/tpAj23bGjsbDuCyVTuwu7kTNZVR3L1wKo6eWMqJh4xqqF0SRKhbElSoXRJUqF1CCBk5OOcSEkyGu/v5RVrryVrrsNa6Rmv9a631x7TWh2mtP534GbBDEwD2tvf0TjgAsLu5E5et2oG97T05/QyE5BpqlwQR6pYEFWqXBBVqlxBCRg7OuYQEk3x3Px80PXGrd8Jx2N3ciZ64lacREdI/qF0SRKhbElSoXRJUqF1CCBk5OOcSEkwC69SMhEzUVEZT7qupjCISMvM0IkL6B7VLggh1S4IKtUuCCrVLCCEjB+dcQoJJXrqf54Kq4gjuXjg1o+ZFVXEk30MjJCvULgki1C0JKtQuCSrULgk6P9382oi/5/dmHDvi70nGBpxzCQkmgXVqGobC0RNLsXHpiexORgIFtUuCCHVLggq1S4IKtUsIISMH51xCgklgnZqATDzVpQX5HgYhA4baJUGEuiVBhdolQYXaJYSQkYNzLiHBI7A1NQkhhBBCCCGEEEIIIQcndGoSQgghhBBCCCGEEEICBZ2ahBBCCCGEEEIIIYSQQEGnJiGEEEIIIYQQQgghJFDQqUkIIYQQQgghhBBCCAkUdGoSQgghhBBCCCGEEEICBZ2ahBBCCCGE+LxHvAAAIABJREFUEEIIIYSQQEGnJiGEEEIIIYQQQgghJFDQqUkIIYQQQgghhBBCCAkUdGoSQgghhBBCCCGEEEICBZ2ahBBCCCGEEEIIIYSQQDGsTk2l1L1KqUal1Kuu+8YppbYppd5K/K4czjEQQgghhBBCCCGEEELGFsMdqXk/gNPS7vsOgKe01kcBeCpxmxBCCCGEEEIIIYQQQvrFsDo1tdZ/BLAv7e6ZAFYm/l4J4JzhHAMhhBBCCCGEEEIIIWRskY+amhO11h8k/v4QwMQ8jIEQQgghhBBCCCGEEBJQ8tooSGutAWi/x5VSlyuldiildjQ1NY3gyAgZGtQuCSLULQkq1C4JItQtCSrULgkq1C4hY498ODUblFKTASDxu9HviVrrFVrrqVrrqdXV1SM2QEKGCrVLggh1S4IKtUuCCHVLggq1S4IKtUvI2CMfTs1HACxK/L0IwKY8jIEQQgghhBBCCCGEEBJQhtWpqZRaC+BZAEcrpXYrpS4B8DMApyql3gJwSuI2IYQQQgghhBBCCCGE9IvQcB5ca32Rz0MnD+f7EkIIIYQQQgghhBBCxi55bRRECCGEEEIIIYQQQgghA4VOTUIIIYQQQgghhBBCSKCgU5MQQgghhBBCCCGEEBIo6NQkhBBCCCGEEEIIIYQECjo1CSGEEEIIIYQQQgghgYJOTUIIIYQQQgghhBBCSKCgU5MQQgghhBBCCCGEEBIo6NQkhBBCCCGEEEIIIYQECjo1CSGEEEIIIYQQQgghgYJOTUIIIYQQQgghhBBCSKCgU5MQQgghhBBCCCGEEBIoQvkeQKCwbaCjCYj3AKEIUFQNGPQLk0FALZEgQt2SoELtkqBC7RJCyMjBOZeQwEGnZn+xbaDxNeA3FwEt9UBFLXDhWmDCsZzoyMCglkgQoW5JUKF2SVChdgkhZOTgnEtIIBnU2amUqsr1QEY9HU3JCQ6Q37+5SO4nZCBQSySIULckqFC7JKhQu4QQMnJwziUkkPTp1FRK/UwpNT7x91Sl1NsAnldKvauUmjbsIxwtxHuSE5xDS73cT8hAoJZIEKFuSVChdklQoXYJIWTk4JxLSCDpT6TmDK31nsTftwCYo7X+GIBTAdw6bCMbbYQiEoLupqJW7idkIFBLJIhQtySoULskqFC7hBAycnDOJSSQ9MepGVJKObU3o1rrFwBAa/0mgIJhG9loo6haamo4E51TY6OoOr/jIsGDWiJBhLolQYXaJUGF2iWEkJGDcy4hgaQ/jYKWA3hcKfUzAE8opX4B4CEAXwXw8mDfWCn1bwAuBaABvAJgida6a7DHG3YMQ4oEX/oku6GRoUEtkSBC3ZKgQu2SoELtEkLIyME5l5BA0qdTU2v9S6X+f/buPT7Oss77+Oe655BzmzQkLVCi6LJFBAWtstpVXIGnQqWlYg+U0gJyUGSVXUUUXWR5lBVdXJSKIig0LZS2YDlYoQIi7lNYsFhE5CCLSCiHNrRJ2xzncF/PH9dM55CZZJJMmkzyfb9evCYzmcMd+rt/c93X4XeZPwGfA/4+8ZrDgLuAbw3lQ40xBwNfAI6w1nYbY9YBi4FbhvJ++43nQfXU0T4KGQ8US1KKFLdSqhS7UqoUuyIi+49yrkjJKWSmJtba3wK/7e85xpjl1tqVg/zsCmNMFKgEXh/Ea0VERERERERERGSCKuZc6i8W+kRr7WvAfwItwBvAbmvtr7OfZ4w53xizxRizpbW1tXhHKjLCFLtSihS3UqoUu1KKFLdSqhS7UqoUuyLjTzE7NU3BTzSmDpgHHAocBFQZY5ZmP89a+1Nr7Uxr7cyGBhXoldKh2JVSpLiVUqXYlVKkuJVSpdiVUqXYFRl/itmpaQfx3BOAl621rdbaKG7joQ8X8VhERERERERERERknBqVmZq4Zef/YIypNMYY4HjguSIei4iIiIiIiIiIiIxTxezU3FzoE621jwN3AH8A/pQ4jp8W8VhERERERERERERknBpw93NjzL/293tr7fcTtxcN5oOttd8EvjmY14iIiIiIiIiIiIgM2KkJ1CRuZwAfAO5J3D8FeGIkDkpEREREREREREQknwE7Na21/w5gjPkd8D5r7d7E/SuAjSN6dCIiIiIiIiIiIiJZBlNTcyoQSbsfSTwmIiIiIiIiIiIist8Usvw8qRl4whizIXH/VOCWoh+RiIiIiIiIiIiISD8K6tQ0xhhcp+Z9wEcSD59trd06UgcmIiIiIiIiIiIikktBnZrWWmuM+ZW19ijgDyN8TIXzfehqhVgEgmGobABvMCvqRUaJYldKkeJWSpViVyQ3nRsiIuOXcrxMAINZfv4HY8wHrLW/H7GjGQzfhx3Pwu2nQ3sL1DbB4jXQeIROVBnbFLtSihS3UqoUuyK56dwQERm/lONlghhMNB8LPGaMeckY87Qx5k/GmKdH6sAG1NWaOkHB3d5+untcZCxT7EopUtxKqVLsiuSmc0NEZPxSjpcJYjAzNWeP2FEMRSySOkGT2lvc4yJjmWJXSpHiVkqVYlckN50bIiLjl3K8TBAFz9S01r4C1AKnJP6rTTw2OoJhN4U6XW2Te1xkLFPsSilS3EqpUuyK5KZzQ0Rk/FKOlwmi4E5NY8wXgVuBxsR/q40x/zxSBzagygZXEyJ5oiZrRFQ2jNohiRREsSulSHErpUqxK5Kbzg0RkfFLOV4miMEsP/8McKy1thPAGHM18Bhw3Ugc2IA8zxW5PfdB7eYlpUWxK6VIcSulSrErkpvODRGR8Us5XiaIwXRqGiCedj+eeGz0eB5UTx3VQxAZEsWulCLFrZQqxa5Ibjo3RETGL+V4mQAG06l5M/C4MWZD4v6pwM+Kf0giIiIiIiIiIiIi+Q3YqWmMORr4o7X2+8aY3wL/mPjV2dbarSN5cCIiIiIiIiIiIiLZCpmpeRPwDmPMk8CjwGbgMWvt3hE9MhEREREREREREZEcBqwSa62dCUwHvg30Al8A/tcY80djzPVD/WBjTK0x5g5jzPPGmOeMMR8a6nuJiIiIiIiIiIjIxFFQTU1rbRfwW2PM74HHgVnAMuATw/jsHwD3W2s/bYwJA5XDeC8RERERERERERGZIAqpqbkE+DBwNG6mZrJj8x+ttW8O5UONMZOBjwJnAVhrI0BkKO8lIiIiIiIiIiIiE0shMzVvAF4AfgL8zlr7lyJ87qFAK3CzMea9wJPAF621nelPMsacD5wP0NTUVISPFdk/FLtSihS3UqoUu1KKFLdSqhS7UqoUuyLjz4A1NYFa3IlfDlxhjHnSGPNLY8zXjTEfH+LnBoH3AT+21h4DdAJfzX6Stfan1tqZ1tqZDQ0NQ/wokf1PsSulSHErpUqxK6VIcSulSrErpUqxKzL+FLJRUNxa+wdr7Qpr7RLgZOB+4GzggSF+7jZgm7X28cT9O3CdnCIiIiIiIiIiIiL9KqSm5ntwNTWT/4WBR4HrgM1D+VBr7ZvGmFeNMTOstS8AxwPPDuW9REREREREREREZGIppKbmLcD/A+4DvmGtbSnSZ/8zcGti5/O/4mZ+ioiIiIiISIk7vuWHI/K+DzV9YUTeV0RESs+AnZrW2oKWhRtj7rTWnlboB1trnwJmFvp8EREREREREREREShspmah3lHE9yqI71t2dkaIxOKEgwHqq8J4ntnfhyEyaIpdKUWKWylVil0pVYpdEZH9RzlXpPQUs1PTFvG9BuT7lld2dtCx601qwz5vRjw6pkzjbfXVSjwypil2pRT5vuWF7Xs5r3kL29q6mV5XwY3LZjJjak1x4tb3oasVYhEIhqGyAbwB97ITGZByrpSqouZd5VgRkX6pvSBSmkq2NbO7u5e6jhc56r5PccjKD3LUfZ+iruNFdnf3jvahifRLsSulaGdnZN+FNcC2tm7Oa97Czs7I8N/c92HHs3DTCXDtke52x7PucZFhUs6VUlW0vKscKyIyILUXREpTMTs19+vwRWW0jdq7l0N7Yt+i9hZq715OZbRtfx6GyKApdqUURWLxfRfWSdvauonE4sN/865WuP30jHOC2093j4sMk3KulKqi5V3lWBGRAam9IFKaBuzUNMY8lLi9eoCnXlqUIypQ0EZTCSepvcU9LjKGKXalFIWDAabXVWQ8Nr2ugnAwMPw3j0VynhPEijALVCY85VwpVUXLu8qxIiIDUntBpDQVMlPzQGPMh4G5xphjjDHvS/8v+SRr7a9H7jD78oJlUNuU+WBtk3tcZAxT7Eopqq8Kc+OymfsusJO13eqrwsN/82A45zlBsAjvLROecq6UqqLlXeVYEZEBqb0gUpoK2SjocuDfgOnA97N+Z4GPF/ugCmGqGrCL12CSy2lqm9z9qobROByRgil2pRR5nmHG1Bo2XDir+DtCVjbA4jWp5ZG1Te5+pc4JGT7lXClVRcu7yrEiIgNSe0GkNA3YqWmtvQO4wxjzb9ba/7sfjqkwnodpOBzOvg/iUQiEMNXTtJOjjH2KXSlRHpYG0w4mAiYMNFCUcsqeB41HwLkPamdeKT7lXClhnmdoqBnmLKFi5Fjtni4i453nYbJypVGuy6TvAhmDCpmpiTEmDLxmjPnPxEN/Bm6z1o7eVmC+D63P9x11bjxCJ5aMbYpdKUXJ3XNHKm49D6qnDv99RLIp54oML8eOdP4XERkr1B7NT98FMkYVslHQEcCzwHFAS+K/jwF/Nsa8e0SPrj/ayVFKlWJXSpHiVkqVYldkeHQOiYiIvgtkjCpkpuZ1wOestQ+kP2iMOQFYAfzTSBzYgLSTo5Qqxa6UIsWtlCrFrsjw6BwSERF9F8gYVcg84YOzOzQBrLUPAtOKf0gF0k6OUqoUu1KKFLdSqhS7IsOjc0hERPRdIGNUIZ2anjGmT4VyY0w5BdbkHBHJnRyTJ5Z2cpRSodiVUqS4lVKl2BUZHp1DIiKi7wIZowrplGwG7jTGfN5a+wqAMebtwA+BVSN3aAPQbrlSqhS7UooUt1KqFLsiw6NzSERE9F0gY9SAnZrW2m8ZYy4C/tsYU5l4uBP4T2vtdSN6dAMZzu5ksSh0vAl+DLwgVE+DYKi4xyeSjx93XwZ+DGKJ+/pCkLFuf+wIqdwsI0E5V8a7kc6d2hFYRCYC33cb3xS70y4eczk6HoVAyOXowOgteh0yfRfIGFTQmWStXQGsMMbUJO7vzX6OMWa5tXZlkY+vf0NNDrEo7PgzrDvTFbetbYKFq6Dx3bp4lpGn+JNSNVINvaShnBsjfUxS+pRzpZQV0tZVjIuIDJ/vu1x6+5JULl18m8ulw2lbxmOw/Zm+OXrqkaXZsSkyxgzq7LTW7s3VoZnwxcF+uDEmYIzZaoz55WBfSzwGu16CHc/Cntfc7a6X3OMD6XgzlVTA3a470z0uMtIUf1KKfB92b4Pu3RDrcbe7t7nHi2Ww54bvu9x/0wlw7ZHudsezxT0mKX3KuVKqCm3rKsZFRIavcwc8/B8w+yo4a6O7ffg/3OPDoRwtMqKKOTRghvCaLwLPAZMG/cqundCxAzZ+KTXiMe96KK+FmgGmRPuxVFJJam9xj4uMNMWflKKedujeCeuWpY0yN0NZNVROKc5nDPbc6GqF20/PbCTefrqr9aOlMZKknCulqtC2rmJcRGT4/BgcewHcc1Eq585dMfxcGo/mztHx6PDeV0SAQc7UHIAdzJONMdOBOcBNQ/q0eC/cfWHmxezdF7rHB+IFU7t2JdU2ucdFRpoXyBN/gdE5HpFCRDpTHZqQGGVe5h4vlsHm5lgkdyMxFineMUnpU86VUlVoW1ftWhGR4bN+qkMT3O09F7nHhyMQyp2jAyoPIlIMxezUHOxMzWuBrwBDyxJ+PM+odHzg11ZPc3UsksklWdeietqQDkVkUEzAjfqlx9/cFe5xkbFqf8wEGmxuDoZzNxKD4eIdk5Q+5VwpVYW2ddWuFREZPt/PnXOH26mpHC0yooo5hLu50CcaYz4J7LDWPmmM+Vg/zzsfOB+gqSnrwjWQuJhNTzy1Te7xgQRDruDvWb/SDrsyIvqNXYDHb3B1WirqoLvN3T/5e/v5KEUy9Z9zQ3lybhHz5mBzc2UDLF6TWoJe2+TuVzYU75ikJCjnSikaMG4LbeuqXSv72YCxKzJGDamt6w0zlwaCblOgs+8r/d3PRcYgY21hq8aNMf/a3++ttd8v+EON+Q/gTCAGlONqav7CWrs032tmzpxpt2zZknogHnO7k61dmrqYXbTaNeqUIKS4hlIvdh/FroyS4sftWNy5Ubufj0fKuVKqhhy7feIWFLuyvxQ356b5nx9/djhvnddDTV/I+7uvzzliRD5TxiS1F6RUDSt2JdNgzs6ZwAeAexL3TwGeAF4c7Idaa78GfA0gMVPzy/11aOYUCLoEoxEPKTWKXSlFY3WU2fO0KZD0TzlXSpViV0Rk/1HOFSlJgzlDpwPvs9buBTDGXAFsHHRnZDEFgjB5+qh9vMiQKXalFClupVQpdqVUKXZFRPYf5VyRkjOYTs2pQPqWspHEY8Nirf0t8Nvhvo+IiIiIiIiIiIhMDIPp1GwGnjDGbEjcPxVYWfxDGoQxVkvN9y07OyNEYnHCwQD1VWE8T+USpC8/Hife0YqJ92IDZQSqG/AC2olXJCffx3a24sd6iZkQXaE6JleUKb9KwZRzpWSNcFtXbVcRkZRxlxPHWH+JyEgouFPTWvttY8x9wEcSD51trd06ModVAN/H7ngWk7brrV28BtN4xKicqL5veWH7Xs5r3sK2tm6m11Vw47KZzJhaU9qJUIrOj8fxtz9LaN2SfbEbW3gbTD1CF9kybg25kZiW6wPtLQRqm+iet5JXqg/jbfXVyq8yIOVcKVkj3NZV21VEJGXc5UTfhx3PQtp3CIvXwCj1l4iMlMFWva0E9lhrbzbGNBhjDrXWvjwSBzYQ29mKefgqmH0VVNSBF8SEq7Htr2BGoajvzs7IvgQIsK2tm/Oat7Dhwlk01JTtt+OQsS/W0Uo4eXENcOhHCYbKsLtb9l9Bao3ayX6U3UicfUQD//XJ6VR4cUwwDOVToHN77qLsXa2pC3qA9hZq717Oqyf9gp3lTcqvMqBYRyvhVzbD8nvB+mA8gs/fT6SqgfDkaaN9eCJ59WnrdrdhHr4K+8n/wtQMoQJUPAYdb+7LtR2hA9R2FRFJeKuzl2sfeJ4ffPIgGisNO7os1z7wPP93/ntorCnP/aKsvDqmNhbqak11aIK7vf10OPdBbbIp40rBZ5wx5pu4HdBnADcDIWA1MGtkDq1/vu8TOPYCuOei1MjDvOsxD10BHTtg4Sq3U+9+SiqRWHxfozBpW1s3kVh8v3y+lA4v3pv6cjlmKcw8F249DZOM45GOXY3ayRANdbZl+qDPMYdM4qpZQSqbZ6fib+EqeOS78MLGvudALJI6X5LaW6gN+8qvUhAvGIK3/QOsPCUj5rxgaLQPTaRfOdu6c1e4xwf7ZvEYbH8G1p25771qFq7iH99Ry+1PptqvaruKyETl+3GumhWk/t4F0N7CIbVNXHXKSqK+n/sFOfLq/u6D6FeeNjSxSO7ni5SowfRgzAfmAp0A1trXgZqROKhCGBtPNfLA3d59Icy62P287kw3atIf34eO7dD+qrvNl7AKEA4GmF5Xse/+4vcfyJ+/dCQH2e2we5tLeiJA3AvDjDmwaDV89CuwfllmHA8Uu/GYi6ldLw8ttvKN2nW1Du0PkgkhOdty/vWbmXX1w8y/fjMvbN+L79tcT87IrdZPDfpc+8mDqb93ed+YP/r0zPsdb7r3McY1EtPVNtEe8QgHtXRYBhaIdqUuOGBfjAWiXaN7YCIDyNnWveci9/hgdbzZ5zww687k2yccwH9f8HfceeY7OeaQSUyvq1BuFZEJqc7u6dNGrb93OXV2d+YTk9die1/P2b5g7xtF6V8YtmA4ZxuaYHh0jkdkhAymUzNirbWABTDGVI3MIRXGWj/3yENFXerneDT/GyRnq910Alx7pLvd8eyQE099VZgbl81kel0Fi99/IFfN8qi69ZOYHx4NN5/kRnHUsSlANFyHPe4rsOky2P1q7jjOF7vJEcGbT4KhxpZG7WQI8pXY2NmZFTc5cusBXS8x+4gGFr//QJqqbf+5O3k/HnXv86uvwNwVqUZZbRPt81ZSPWUa9VVqlEkB/FjumPP1nSxjXL62rh1CWzUezflegb2vc8jKD/L+BxZw88lVrDrnA8qtIjIhBW3uPBm0addl6ddi7S25c/Se14rSvzBslQ1uNV5aG5rFa9zjIuPIYDo11xljbgBqjTHnAQ8CN47MYQ3MGC/3yEN3W+rnQD9Ly4o8W83zDDOm1rDhwllcdWIjXq5Rm4FmjsqEUBl5C5OMj+623HGcL3ZzzLQYdGxp1E6GoOASGzlyq7d2Cf/1yen828fqMbte6j93J+97Qfc+L2yE31zpasqdswn/rPuwjUdokyApnBfMHXPeGFgaJtIPk2emujFDyH2BUO7zoDPR7k3UK357eZdyq4hMSPn6F4xJ6zJJvxbLdx2XlldHdTWc57nyYuc+CBc/425VbkzGoYIi2rjW01rgDuBOXF3Ny621143gsfXLmgCc+pPMkYd518Pma1P1LKr72QBgBGareZ6hoaYMz889ytPvzFGZMIwfhepGt/x88nRYsDIzjvuL3TwzLQYVWxq1kyHILrEB5F6m6PuuA/KsjS7Gp8+E9hYqvDiVAR8eubrPzEsWroKn1mTeD5alYn3bFli7FH4+Gw9LXVW5LrqlcIEQLGzOirnm/gc+RcYCY/rmy7kr3OMwuDJK1dNcbs1+r83Xpp7T3oKJa9WGiExMOfsXTv2Jezwp/Vps87W5c3RWXh3V1XCe5zYFqj3E3apDU8ahgqYpWGutMeZX1tqjgAdG+JgK4gVDEKqAOddAqNI9OLkJe9rPMF5w4J3HkrPV0juIijVbLTkanv3euoAScHF7/BWuBmx7i6uvuXQDNhAcOHaLEVvpo3ba/VwKlCyxkVyCPr2ughuXzcxcpuj7bnR602UZm1rw+A1ul/O4cRu5JWdeVtRBtAsmHwwnfxdmfzu1c2T3zpHL0TKxWAvBcjjjTtcZZC3YuLsVGcushcdvyNj9nMdvgJOuHvymf4Gg27zi7PvcRbkXhPsudYNGScqxIjKB9elfiHZBqCJzY8H0a7FtW1ybds41UH+Y8qrIKBnM2qs/GGM+YK39/YgdzSAYPw7rl/e54DWfeRBqpvb/4ljUdeYsu9vVxXj0B/Dy74o3Wy05Gp69E1p/M0dlwjAAf/k1LFkPXgD8ODy5EvPhz0PNADFSrNhKjtqJFMjzDDMaKvjvCw5ztQi9ILa6InPGZFcrrD2jz6YWLLvH5Vbrp+J37dJU/JbX9e3IT84ozr5g14xiGSRjDGy9DY45A0zAxeHW21zOFRnDTPU07HFfSZWsqW3CLlyFqZ6Wv4zSuQ/m/34PBKFqamIjthic9B2Y8k547IfKsSIy4Rk/Ds9scO2F5DXa1lsxH74o9aTsa7GOHVDVCJMPAePBP10G2/+ktqvIfjSYTs1jgaXGmL/hdkA3uEmc7xmJAxtQPM/y8YGWzcSisOPPfTuFTvy/UF5bnNlq2aPhyZlH/c0clYnDeHDkp+C2BakYXNDsHh+IYktGSyyKl5U7zcJV0PhuSI5g5yvr4QUTudUrPH41o1iKZTg5V2Q0BUOYxnfDWb/aN5hkqqe5nDuUMkr52sCz/hmwyrEiMrEZk6e9kDaAP9C1mNquIvvdgGeYMSZZ/XY28A7g48ApwCcTt6NjqJud5NtoJdJZ3IQTCLp6iVMOdbfqdJKkWC+sX5YZg+uXuccLodiS0VDIJlWF5OXBxK/qAEkxDDfnioymYMjlwCmHutvkINJQ2sH58nisVzlWRKTQ9kJ/bVm1XUX2u0LOsrsArLWvAN+31r6S/t/IHl4/sjc7+dAX3MYUkS5XMD2WZ+MUP5Z7ZNuPjezxiiQVEoOxqIvjXS/3H88i+0shcTsSm1DpXJDh0ve+lLJ8mwENNt/GojoXRET6s79ypNq2IkVVyBSv9C1m3zFSBzIUNliOmXMNTHkH9HbALXMyl9OkL4tM8oK5N5/wNNtN9pOBYjDf8rBc8SyyvxSSO4e4ZNz3LTs7I0RiccLBAPVVYVerU+eCFIO+96VU+T52x7OYtNrCdvEaTHIzoELzbTKXhip1LoiI5LM/2gtq24oUXSEzNW2en0eV7WzFrJ4Pty5wiWagZZFJyeK+6SPb2sRH9iNbVpMzBm1ZjbtfyDJfkf1swLhNGuSyG9+3vLB9L/Ov38ysqx9m/vWbeWH7XnzfDutc8H1L695eXmvronVvr3s/mZBssAwWNmfFbrN7XGQMs52tqQ5NgPYWzO2nYztb3f1C820ylz76A1cfTm1gEZE+Cm7rDoeu80SKrpBhh/caY/bgZmxWJH6G1EZBk0bs6PrhR3sJJJOB9QufKh4MuZGQtKLrJIuuZ4vHXILRhixSRH73HgIv/hqW3+ti13jw9Dr89ywmUFHb/9IH33c7nqr4tOxnfs8AcTtEOzsjnNe8hW1t3QBsa+vmvOYtbLhwFg0DnQt5Yj/ZUZp83+l1Fdy4bCYzptZk7tYuE0OkE35/EyxZn9rN9LHr4CNfHu0jE+mXH+0lUN0Is6+CijroboPN1+LHegkM6o0SuXTranc/eS4Ey6D6wIFnB6ntISITwIDXaEX5kEEscfd96N4F0W6wcQhWQJXyr0i2AXvorLWDajftLzEvRCA5Pdx4hU0V79MoOzh/UojHYPszfaeGTz1SHZsyLHEvROD1p6DxXamLlNefIv7eM91FSn9LH3Y8C2nL0Fi8xi0/05ebjLC4CRHYugoe/nbqwdqmVNymG8QFcCQW39ehmbStrZtILJ7/XIhH3bmQJ/b77Sit0ey8CccLwsu/S3XogIuj4746esckUoB4sJzA8VfA3RemvvfnXU88UJ7Ku4Xk2/RcunW1+6+2yQ0itbhfAAAgAElEQVTwF9KhqbaHiEwAMS93WzeWq63bn/7ycqFL3H0fdv0V9r6R+R2g/CvSx6icDcaYQ4wxDxtjnjXG/NkY88XBvscuJrH7tHVwxnqwduAl5clG2U0nwLVHutsdz6YKrmfT1HAZKYEwHHcJbLrM1YHddBkcdwkmkNixNF+JhHBV6qIC3O3tp7svTZERZrwAzLs+My7nXe8eTzeYXOv7NHp7eOxzh3Hnme/kmEPcxP/pdRWEg4Hc58KCZreEMiv205ebd0dj+TtKZcKxocqcy88JVY7ugYkMxI+nLmbB3d59oXscBsy3yby4O1SPHWrppa5WtT1EZELYxSR2nrIyI1fuPGUlbQxiYepA7eBCS+F1tULbX/t+Byj/ivQxWlMOY8CXrLV/MMbUAE8aYx6w1j5b6BuEPI+yqhqonuFGKiYdhD1rI/hxTK4l5fkaZec+6OoQZYtHc08Nj2t3MhmeULwTHvle5nKyR75H8KTvAPV5SiRMhd2v5o7JWCT3B2m5mBSRF+uBp2/vs4TX+8ilmU/s3FFYrk00+kIPX8WBR5/OgTUNrFt0MN9/vI6572uivioMnkmcCxsh1ptaNpyccZeI/ezl5jef9QGm11VkdGzu6yiVCcf07oEXH+iznIyjFkBV/Wgfnkhenp+7Ler5ibZoZ6Jtm75Efe/rUDMNv6KeN9s7mRzfSZmJE6k+iHCiXZGznZxPLDK4toeISMnyuOn5MJ9fci/lnk+P73HT7ztYNmsQ10/52sGfeRBqpua4zgtAuNrdpotF3OCr8q/IgEalU9Na+wbwRuLnvcaY54CDgYI7NWsDvQRNEOK+62j0fczTa2HrKjcte9LBmS8YbKMsEMo9NTygXclkmEwATroasO7LrLYJDjzaPZ4UDLnC/0kd22HXS7ljMhju+xlaLiZFZkMV8J7FcNuCjGWQNlSRelI85uIru/Po4W/3zbU97RAqh/9zpVte8+uvE+rYwVcW3YptrErVvgyGXN23W+bkjf3s5eY/fOhFvvfp93DJHU9n1NSsr8pxrsj4FyyHoz6NKwWOuz3q0+5xkbEsEIYZc+Do01ODoE+tcY8DxLpdh+bHL4d7Lkrl5kWriQeqOdDbhcGV8gj+7b/xD3gnHbWHM6mygNhPDozauFsV9cjVsG2L+12+toeISAkrCxq+9IEwwd1/gVAl1dEuvvSBt7MnWGA99njMrSDNruG9dbXL10leAHp2971OO2AGdG53fRte0K3SK/TaT2QCG/XikMaYtwPHAI/n+N35wPkATU1NGb8LeMDuN/vWvIQ+s4L8WAwDmIuedJ1IyeTSX1JITg3Pfn/tECkF6C923ajbK31jq/ZtqedkbVJlA2HMI1fD3BVZFy63uhmY2TrzzExOjhKK5NBvzsXPuQwy8JkHU0+KdMDu1/vGdnhSZq6Nx1IlPZLPm7sCfnMlZu0ZmHMfxK9sZGdnhEgsTmV4MrWL16R2AU42/irqoWM7ddEefvDJg/jWb1vZ+uoetr7aznfvf4G15/8DAOFggPqqsDYJGsf6zbnBMjcw1CfnFqnov8gQ9Ru3QCCUKFezblla7Da7x8ENhh53aapdAO726TsIHnUaJivmvbdeorryAKicnv+gfN+1ISIdbjD1kauhY4crP/LQFe7nxWtytz1kwhgodkXGqv5it8bfQ7C3DTZ+aV/uDJ52EzXltUABg0E97X3bGwuaoXxK5uSVXCtIH74KPnYprF2alrdXw6LVmY8p/4r0Yay1o/fhxlQDjwDfttb+or/nzpw5027ZsmXffdv+KuaWk/uOXCy/F37wXrj4Gag9xHVo7ngms2G3oBme+QW8d1H/M9e0+7k4w+oJKTR27Vm/wtQe0neTqhlzsLO/jendC1073eie8SDaBQe9D6oO6PuhbX9z50G2L/4R6t4+nD9HSkdR45b2V11toGyJXOue05J7RuVZG2HSdJdrfR/2vAa58vfsq2DtUuzFf+L57tqM3ctXnfMB3l7ehYknyilU1EPr8xmj3DtPWcm593ey9dU9TK+r0MZApavIObcFkyMu7VkbMbW6GJeiGnLs9sm5gG3fhrnlpByxex+mdjp0vuVmb66YmflmFz6emlWf9jrO2oj145gph+Y+iFyrPBIDTnTsSGwspHI241Bx2wtp/ufHnx3OW+f1UNMX8v7u63OOGJHPlDGpuO2F3dswN+fIuWffh5ncz2AQJNq32/K3g0OVqWu2XG3qRavdPgvZrz37Pjf7U7ufjzeaaVFEo3ZGGGNCwJ3ArQN1aObkx3IvJ7c+1DbRS5DWvb3Q8WaqQzP5nPXLsMeeP/BS3EAQJk93M+gCIbf7WMf2/JsLiRQiX+z6Mfdz+iZV02fCsRdgmufCDR+Be7/gRvq8AHbKO92yhvR49H0Xo8ZLFaBOqm3KHCUc1DEn3rf9VZ0DE1UgnDOmoibEa21dtO7txfrxPLEdd7k2FnWzlGO9uZ9XUZf4DNNn9/Izf/573qLWdaBWT4XunX1GuevvXc43Ptag5eaSqb+4FBnL8rZ1E+2Fiim5c7MXzB/z+coo+b6rx5k9e+iei2DWxanHqqfqglpExqeh7qmRHBDa83r+3FsxJfVYMEfermrI/9m1h7hJKTXDzL/j/XpuvP99ktdo7X5ugJ8Bz1lrvz+k9/ACeTtt2uetZPGt/8v86zdj8hRZd4V5C/jzB7trushA8sWuF3BxFU+r/zrr4r7Lyu76LPTuxVz3PvhZWjzGIm6EsGev+/I87aY+O1WTXv+wUDoHBFx85tj9/JW2XmZd/TDzr9/sLqRzxnbQzUDesy018z3X86JdblaQgYbqzAvvPruX56mT/N4DK9lw4SxmTK3RcnNx+otLkbHMyzdA6aV+P+lgV4omPTfnumCubcJ6AUyuMkrJAadoT/8DTqrjJiLjWX/XaP1JLifvbM3f3kjvd6hscMvI0/N29dTcry3Wfh7j9XpuX0dmi/seu/dfxtffJwUZraHWWcCZwMeNMU8l/jt5UO8QqkrUxEpLBgtXYcPVnP0rt/xwW1s3vsmXnIKF9eTn2zW9q3VQh7vfaaRi7MoTu4SqXFzFY6nfVdTlvsAIVaZ+vv106N3jNltpfd7N9Nz5IlQ1wqdvhs8/AXOugZoDM0cJC1Wq54AUV7QbWh5zJT6+sNXdtjxGme3hmEMm8YNPHoQNhF15j/TYXtDsahr2tLv/bj0N7jynbwfpwma3ccvjN2Ai3Vx5QuaFd5/dy/NctAfDZTTUlKlDU1JClXlybuXoHpfIQIwHp/4kM3ZP/Yl7PNm2CwRh6pGulvzFz8Cye+C5X/XNxQtXYaob+5ZRiseg9Vlongutz+UfcFIdNxEZ77xwzgF8vHD/19PJgfbN17rB+ez2RvZgkudBw+FuafkXnnK3kw7O3VYp1n4e4/F6LqOj9ij3PXbsBW6l43j4+6Rgo7X7+f9juHUEbNzVpVj+S/dzYkkuNs7WV/fse9ruqMeUBc2wPr3I+irXILzphIF3hh7sruljgXa+HtNsPIopn5wZu9Z3j/tRePQH7mJk/TJXKyvXrnfdban77S2uw6mzNaOwNfOud+UTAA5879BrYJXiOSDFF66Cw06EladkbFgR9CZz0yc6qb93gauJ2fJE5q6PW2+FWRdho12Y5GYX7S1uw4k510D9Ya4T/ldfdjXbFjTDoz9gxj9+hel1Ffl3L0+OcmfnOV10S7Z+2gsiY5oJuhUWc65xnfDRLghVYEwQdr0MkS6YfIjrqKyeCnu3p+oVH7M0kYuDbhAoXOMGjrJ1bE9tQpG8IM/ekHDSQW5QVG1IERnvwlWZOTdchcHCTSfmv55ODrRv2+JqEM++yi0nn3Sw65QMZs229P0+deHde7/bdXCOxH4e4/F6LldH7T0X7avRX/J/nxSsZNde2Vhv7o2CzvpVxvNea+tmyq7H3cVMPOqWnW+9FfP3/weqG1MX2Lefjv3Mg5jsnaGTSSr7c8byEpx8IzFpO8LL6PGD5Xg97bC7JfWFObkJv7wOzzfw8u/cE5esdxczC1fDuqWZnZUPXZF6w9om8KM5d6Zm+S8hVD68f/dSPAek+KJdqR14IbF7+TIal28kcPvy1AXxxy9PbVBR24S/6Db8sjoCkdcyY2jbFrh1gRuhnvION/vIj8Nj18HLvyP08cvZcOEsIrF47t3LPc81LM990DVYtHmF5BPrzb0xVVZ7QWTMsXFYv7xv7C67B34+O9XpOPVI8DxsrBuTfO7W1e4/gHM2Qa7NgXwfYmlLztMvyBve5doPNQe533W1KteKyPgW74H7LnHlv0KVrv1w3yUw/6f9X0+nD7Rv2+I2/Fm8xnVq5sqV/V2rD7Qh0VCNx+u5fB21FXXu51L/+6RgJdup2d9mK7OPaGDTs61Mr6ugeso0bMNszMpPZj7/ubtSvfiJ10YjPQR9m3nhXIqzgcbjSMw4Eoh0wENXwtGnp74wH7qSwEnfdbMhkvG2dbWLt6Ub3MV3+yuuYz5U6Wa0TZ8Jx10KyQ2D8m2cNdxYLcVzQIrOxqOpi+Wk9hY8G895QRxreDd/3B7hzy8FObPsNYyN525MeQHY1ZIxM8guXkO7N5lIJE5l2KPWb8fsyXEx7XkaqJGBDbQ5m8gYZf14zrxL11upn9eeAWf9ChuqSG0SmJ1nq6fm/s7uaoVdL2W+JnlBvuweN0uoe5fb/GLtGVr9IyLjmwm4a6xk/wBk1rXMdz1dyEC776cGh2ye67aRvFYfj9dz+TpqkysdF91a2n+fFKx0OzWTG01kBbHxQvz4xAremvdPGM/N7jF72vvvxU+89oW3IkwLR2ioKUs9XoqzgcbjSMx44kehc3vmY53b3eP54q2rFe76HPt2RJ/3IyirSc2cu+C/c/+bhyqGH6uleA5I8QXy5JXsxxMXxH88cT2nrXqJrf/6XkzHNti6ytXNTMZsshTIH2+HFze5QaaKOmzt2/hbtJYzVzxKQ3WIm0+uwty9vP+L6fSGouJTsuVpLxSt+L7ICIkQojxX7O59M3U/0clpoj3w6HV9l48vWAnlk3PnxFgEHrk6x5Lz1W6GUevzbkf0ZGmb5Odlz1ZSDhaR8cAYt3Lors+m8uGpP3GPQ6rdm0t/A+3xmCsNlxwcOmP9/r9WH4/Xc7k6ahesdGVXlt3jyrOU8t8nBSvhTs0wLLkDdr+StoT3bRAM461dQmN6YysYhhlz3My4ijrXe//UGvcagNomdp6yksvvf5MVSw7u+1mlNhtoPI7EjCfBcjjpe6mZFsEydz9Z6ypXvGUvazBe5lLgjf/iNgW64+y0f/Pb3GZBxVBq54AUnTUBzIKVLm6TObfyADeqvXgNPHyVy7FVDUQrG1n/cDsAFV7M1XtNL6vgBcBaN5P44W+7x9cuhdomImf9mr/t7KahuoxvfKye2rsXDHwxrRrC0p987YV8FyYiY8QebzLR+c3UbEgfDGqG3r1ugHPbFvdYxRTofAE+dKFb0THvRy6+K6YQxxAor839AcGwm5WUXHJeUefOj0kHQ0+by6un/rj/GUXKwSIyXphAzjrGmKAr41F5wOAHROMxNzgU7XJ5dvO1bjBp3vWp0mH761p9vF3PZXfUGpOom+6VfoetDErpdmr6cehtz9wY5bSboHxS3+nbFfVw3Fdg3ZmpOm8LV/EajTRc9Ef+1h7jlj/s4coTpjGNt6CjbN+J4PuWnZ2R/HXdxqLxOBIzrhi35Dw9duf/lH73zkr7N7W+D9GuzCVp27bA/ZemasTp31yKzNiY25AqPW5P/QnYGBwwAz721X0j0KHaJr52ajNnve8IQgHPDSIlZwIlyirYRbdCqBJT2+TqGx93KfG6d/DyW53c/sQuvjx7BtPL2gZenqMawjKQ/toLImNYOOhRUVHtOharp0Lby6lN1eaugMdvgOMvh56s+J67An79dfxP3cSesgOpy9cWSB8wTQwssehW97tkKaN8GxYmZxR1KgeLyDjh56ljfOqP4ZY5qRxZXlvYNVYsCq3PZZbvmLvCDSQ9dEXqui3ZGdfVquu3wRpvHbUyJKV7xvgxuPPczEbUnee6x8/Z5JKD77vfde9MdWgmnuutO5MdbXs44Wd/pd1M5qsz4aj7PkXgB0e5XdF3PIsfi9HT/gaxXa/w5ustfGPDH3lh+158347O3zwYyRO89hB3q+Q4dvhR2HB+ZuxuON89nvE83+1K2v6quwX8igPw/RgmWQMrXceOROkB/ZvLCLA2tRwH3O1dn3WP730j1WBL/G7yXcs4fFKUQPdO+OiX3cX37KvgnE3YZfcQb3gXZso7sOc9jJ3zfdj4JQIr3s/hv5zPVbOCND/6V8JlFX3jPHt5jmoIy0D6ay+IjGGV0TaCt33KdSyu/pTbXG3bltQOryd9x632SO7yCqnfHXcpmACTK8ryf0BywPQzD8I//8HNTtr4L3DjP7l29BnroWYaLP2FW/EEmTOKfB8iHcrBIjI+5KvBnf7z2jNc5+NAYlHYs61P+5h7LnIbEXXscDPqe3bDzSfB9w/f1wexrw+jmLKvK0fiM0RGSQnP1MxX+D+auSPkpIPyXvQ2Vhq2tXVzzJQYZSuXZyach6/CnPQdKjtep7KrlQOfXsNVs77MZQ88z7fmvzez7qbIYPgxNzMtudSru80tRUi/wM61nGvpBkwghBePgheCT98Cd5yVVgOrn2LIQ6x3VZIzlWVk5Clqbjpb3ZKa9N9Nn+kabMaD3dug5Qk48UqsFyQWKCdQ3UAwEAAgFosRyrogr793OeefuJ7XI1UEF6yjpuvV1DKgundkxrlqCMtACsm5ImOQ50dSNeDzXWh3bM/9u7pDMWXVmO6dbpa9jUOwAqqyvv89zy0UWXVq6n2mz3QXvumzPxeshJOuBozbFR1ybzQEysEiUpoCwfwbzyQVMmgTj0HHG/nzc1WDu27zAvlnuif3VCjGqkuVCZFxrnQ7Nb1A7qRjgq7A+eZr3cjInGuw9Ye5JY5Zz62rKuOxzx1G2Pb2vSA/9gLMLXMyporXP/6fnP/+y4nE4vvv75TxJ1gOx1+RWUdl3vWpmprQd0ltdSP07sEk6xn6UXcOzPuR6ziKdrnn5DLELzLft7ywfS/nNW9hW1s30+squHHZTGZMrVHH5kSUb1fdPa+lfm5vgWOWwsxzYX1aDbhTfwIPXA4nfYfQ5Gn4vmXH3h58P87UWGfOBt+B1R7BmjKqumKZF9aL12Q+VzWEZSCF5FyRMSjuhQmm7+Sa3ul43KVud/Ty2py52QbLMF273Ez67Lpt2d//2YP/sy7uu6Jk/fLMJZhLN7hZolUNrsNzfWpDN7toNbbigBJeDiYiE1Ig7Gq/725Jq8HdBI9dl3pObRNRE2JHW1fuCR/J665olyvPkavtPOkgqDnI5efsNnB1o3uP7c9kLlsfTiekSjXJOFe67Q0v5OoQJpcmJusS3nk2bLoMTrjSJYVQJWbT14ktWJ3xXH/BKqofuowDb/4AZudfMpc4zro4tQskpKaKH306B1Z7hIOB/fu3yvhi46kLDHC3d1+YmAmXtiQg/Uvu+G9CpNN17twyx9327nW/u+tzECiDX/5r7iUL+b7IBlg6sbMzsq9DE2BbWzfnNW9hZ6eWlE1IJuDqAKXn3AUrYfJ0CFe7mcMz5sA//kuqQxNSy9Q/eB74cfx4nBe27+VT1z/Ka9tezV1KobaJ2ppqGry9eGuX9B+76TWEL37G3WrkWdL1l3NFxrCeUB124apUXeLaJtehefwVsPFLmB8eDQ9dCQuaM3KzXXQreGG3hDw79m8/3W1akdbesIFwZh7ub2YouPb13jfglpPhpx+D3/2nW6J+7oMw5xpe6q1lZ5dmQotIifHjbhAp/Xor3uvatmdthDPWE1/yCy66u4VZVz/M/Os39y1N19XqOiM7WzNzN6RW1tUc5GaFBrNybzK/b/9T32XrBVy75aVSTTLOle5MTWNcoyt7d7Ljv5mYudYJJ/+nW/r4wkb4xNV0LLmXSDTOpMowwfsvdY9D3x3IqhryThWvra6mvEpLamQY8pROMLEI7Pizi7/qqfChL8BjP3S/n3QQrJrf96J8+S/diOI9n3d1trb/qe+o2xC/yCKx+L4OzaRtbd2aqTxBxaxHKFkXs2YaVNbDpm+4PFrb5C6qT/4e7H41d7xNPhiz80VsbwfXPtDtZv9OCsCmq1ObCKXN8glPasR05BjBzhW7KhIu/YnnK1ejThcZ2ypj7ZhHvgtHn+42tlqy3l0EN89LxXSyLbtkvdswqHoaxCOYn5+Yf+fy3dtSpZoWr2HvpL/DpO+yHu3qfwnmrIszO0tf2OjaH3OuYad3AJdsbGHFEs2WF5ESk73vQXUj9OxJ1S2ubcIuXM2Ovb1AasLHvRd9mDp/N8S6XT9EdaNbNfrxy1M15asaErunh91zoO9qo+Mudbk1X+4eaiekSjXJOFe6U1niETc6HXNJhVgvPPJdiPWkRlaMB3+5H2qbCL75FNW3ncJk04Fn46lGYLL2W6jc7UD2r8+7mUc5Zg7Z6qmUT56aOcU8HnONw10vu9u4LpJkAMZzM9oWrXajfotWu/uBoJtl/PPZ0DwX3vNp17EJfWdugrtv46kOzeRj2V942aOAUNAXWTgYYHpdRcZj0+sq+s5UVuHpCaHdm0zsuK+6GN37pruoTubR9hb43fdcPFY3us0lps9Mvbi2yS31ffZuvLVL+OHJU7n/3BnUV5e7Qum/udI1+M7a6AaqqqcSDOYYwd73XmqEySB4gdw512jVhYxtJt7r8uzapW7X850vuplE2SWTjj49UXPtAPA8zK2nueckl62nq22CqgPceVDdCLefTnmkjb96b+NPJ/2CV5c/wf+GZhBbeGvm7KJ517uLdMg7k7O39u849/5OWjuiI7OqSe0NERlJ2fk1ewCnvYXguqV842OpQZsl7z+Q2t43oO1lePNPcN9X3WxLcO3bo093HZrltXDXBbByDrazlda9vby2u4e2mr/Dfiax2uiAv+8/dwfCQ8uByc7T9JyuUk0yjpTwTM0AHHtBxuwe5q5wI9ngHlu71F0gf/B8eOKn0N5CYN1SOONO9/zqRrdMPbmjb20TLL4NGt7Vt0bbolsxkw/BBNIaafGYq3eR3Fm9tgkWroKpR7oOKpFcAmXw0Usyaw4uaIZoT+ZMzLVLscvuwRx7nptRdMZ6N6s42YFZ2wRdu1L3k49ld/gMseZgfVWYG5fN7FNTsz59prIKT08Y0Thcs9Xj80vupSroY3LUISa9DvG86+GhK1yn5YKViUbe5TDrXygzUQ63f8UPHJWapbl26b48bmxiGY/qZUoxBMK5c25AneMyttlAmYvXQz8KMz/j6lbOvio142b6TDcTKL0tvLDZtW/bW1wnZNZMeOb/FDZc4HLz3BXwmyvx/Cifv+25jNUZn/vI27jkrPvw/Kg7V6Ld7jWQdybnMzsitHZE+7YVikHtDREZacmcm8xteQZwDq0NAbD4/QfyuXdHMM0LM/sj/ufHbtblrQvcZIC5KzImoUQjPcy/aXPWngWNeF073Hvkyt2L17jSY6vnDz4HppdqKmTjoSFuMCsyWoy1duBnjQEzZ860W7akOm9s+6uYW07uO416yXq4/tjUY59/Ah78d3fB/ZsrXTI5/7dgLVgf7ji773t85kE3opI8mY1xnaiel3lS794GN5/U9/Vn3+dme8p4MaxdcYYcuwDnbAIsdL6VWraw+b/g5d9hF63G+PGM4vx5v9xGavfzju1w0wl9/xYVnh4Lihq3b7R3Et75AvX3Ji6qN12W+ndftDrzPrg4OPMuCIRcZ3zr8303a1m0Gp6+A5o+mNqV+qk1cPJ3UzlUDauJqMg5tyW18V9SbRP2rI1uE0GR4hly7GbHLUDrnm7K9/6NmsoqeOt5V27JC7oZP7ct6JuLweXWOde4i2nYt6kQ9X/n2r0bLsgcHJ1zDb0NRzHjO3/Y9xbHHDKJmz5R5fJ9Ml8v3QBlNW6lVKjC1dS8fcm+3/uLbuOtyndivBxthWJQe2MkFTXnpvufH392OG+d10NNX8j7u6/POWJEPlPGpOK2F/a8gdn7BiQ3Zq1qhOTM96TaJuyye/jxH3r43MyqnO0LZl/lZl0Gwm6GfdaklD+d9AtOufkv+14yva6CDRfOoqEqlBq8qW50uXvKO13tei8AN/7TyOdADSDtL9p1t4hKdzph9vRwcPcje1NLyqsa3FLff/isSypzf+SWrO/eBvWHuQvknPUqulMdmP2d1PFo7tfHoyP7t0tpyxe70S73c3r8Vta75//i/IyOIPtP38Bs/BJ0bnez4Crr3dJfL+SeX6QvHc8zNNSU5X+CCk9PGFPYQ1nyAnfztVm73b7NNeCSHZObr3WNt+5dUDEF3rPIvUn2hhVrl8Kye1y5hfYWtyR49rfczOSO7akOTF2wynD4ibII2THqqz6wjG1dUZ9YoJaanh2urFLyIrfyANfJaMj9HVx3aGq2UccOqDwAG4ti7rkwc3VHewvU/x2BQJC/XHIk1o/z8m4fTID6e+dm5uvV893Fc+0h7qK3uz2jrr0XqqCxpnzkLnrV3hCRkWbjbuAoqXsnLFwN61I1NZm7AvP7n/O5Y89z+yHMvirV7oW0/TlegYPe5zYFSs5yr20ivug2Lv/Fmxkfu2/PAq8s/4zK9jw164udA7VTupSg0u3U9AK5C95OboJP3eQuiDtbYfMP4cP/DL/+OlRNhdnfTr3ej+d+D2tTs4P6O6kDodyvD4RG/u+X0pUvdqsa4Jz7Xew99iNXgwXcxcuhH4Wtq/d1BJnlG12HZsPhgIGVn8wsgdD4bggm4nAkR9xUeHrCCPppgzjbtsCWn7ndbqPdLmcmZwsll948foPrbPeCLicGy90FeXWj67SvmQbhGleqY/m9bgDKj2VsPuQvug0aj8ALqPahDEOoAk76npt5ARAsc/dDFf2/TmUXCxMAACAASURBVGSUVQQNDaYHmpe63PmJ77qL7I433UBo4xG5v4M7tqc2pqieig1V8WZnnAM7dqQGTivqEptsVhJ86/l9g06H1zbhL1ydWsKe1N6SqmkZ7Ya2v/YtiTOSF71qb4jISPOCEOnMHESqmurqcVsA60rPHTk/NUMz2e5NrgitbYKaA93r/bi7VkvrpNxjJtPa8WjGx2bsWZBvMH9/5UANIEkJKt05xIGQq9mWXvB2wUrX0Gue6zZb2XSZW3b+6HVuJ/QT/901xrY/4+q7xXpd7aH095i7AjZ9HbpasQOd1NXTXAdS+usXrnKPi+QTCOeOXT8GFfWuQ/PYC1KbBq2e72ppJTdeaW+Bva+7pbwf+XKqTlzyd+vOdOdBUr7O+a7W4f8tKjw9YdjsTXu2roYXH4KK2tQINrjbey5y+XbTN9yy82AFPPI9+D/fcnWMN13mlhHetgDaWuD+y9xma5u+4WJ/+kxob8Fbu4Se3dvx/dIokyJjWPIiJbmRYKRztI9IZEB17MZ0bHd59fhvuk7I9DhufxWWrMtqh652g6cVddC7B7p2YX55MXXRHcSW3evaDpsuSzsXOvrMovfWLXUX8+lmzHGTBW46AX7wXvfaj1+e2TbJvugt5sY+am+IyEiLR12/wbwfub6DjV+C645x+bLtZbj/a24wKblSCVLt3lkXJ3ZHX+We98Nj4GcnuHZwZYOb5V49lckVZdy4bOa+zVhz7lmQy/7KgdqkU0rQqM3UNMZ8AvgBEABustZ+Z1BvEO12m1CkLyfr2Q33fqFvkpl9lZvt1vqcWyYTLIOPfMktRZ9zjatlGNnrdvRNjLLYk66m2w9Q2d+ISCDoNgU6+z6XBAMh16GpTYKkP9GuVOzWTHO1sR74ppudds4mN0MzWRga3O365XDmBtjxnKs52Nnqbk/6Dpz648wlv+0troM0aSRH3AZbeFpK1p5ALd68ldTenaqxZg8/GbPn9TxlOCIulusOdQ3B2d92I+Dp9WTbW9xGbaf8MJWrk7drXUdp+94OQqFI/2UQRPoTj/QtfXD3hW7mhcgYFoz3uu/7GXNcmY/kqgxwtxvOh2V3p9rC0S6IdcHPP5F6k0R9t/I7l9J75kaC2edC51u5c/iUd6ZmBdU2uRzePDd3Gzu50Vv6RW+xV4movSEiI80Y10dQVpNZSzM93yUHmtK1t7iNhpf/EnP/19w1XfLxrKXbnmeYMbWGDRfOyr9nQS77Kwdqk04pQaPS+2aMCQA/Ak4EtgG/N8bcY619tuA38QKuPsXapanHztmUO8lMOtg1Cjd+KXVyzrve1drc9RLc9Tk3Q/Mv9++rZWgxXPfYLs49ZWVGoXR/0W146Sd1IKhNgWRw0mN30Wq445xU3Ha2Juqw5IjjvW+62RULmuF/H+i723Ry6UPHjsx6MCO9XEE1DyeE7ojPRb/q5Bsnrqex0lBRU0e96XFLbLLja8YcNxM+fUn6wmbXgZ8zRx/kbpO7TFbUud/VNvFGh8+0Sap9KMPg+7njzg5j1pjI/uB50PIEfPQS1zmfK46Tew08+E03sPnPT7rZk+n13RK5NWxifd+jszV3GyFcnXnxnG+AtKIu90XvSNRlU3tDREaSCbjBIT/PvhkVdflzJkDnjlSHZvrrsiaSDLhnQT77IwdqAElK0GhF5weB/7XW/tVaGwFuB+YN6h28HMvPK+tzT5euOqDvNPG7L3Sdnd1t7v7jN7glvoklv94tJ3Hu4RG+9wd48sT1vLr8CZ48cT1vVb5TJ7UMT6DMLTc/Yz00vsuN+iWXb22+Nn8cJ2N1/TJ419y+sznvucgtF8sugaAlW1IExhhaO6KctuolnmgNUe/vwrQ+7zYDWrAyM75O/Pe+OXfdMtdYzBXbyTqz3W0ZtztPWclPn9yTqjMkMhRenrgziisZ44Ll8IFz3Pc+5I7jWK9buXHqT+C8h12JmwUr4Zilqeckcqo1wb7v8dSavjl88Zp99TiTSybzLkmsfZu7+M2egam6bCJSavyo6yNIdlymq21yKz9bnnCTUtJz5qLVsPm/3ASU8bB0O9l5msz/6vuQMW601kkfDLyadn8bcOyg3yVc5ZaPNx7hCvFGu9xsoHXLUrODFqx0U8lzNayMcZ1I4JZJZl2E19+7nAUnrue0VS8BrubFhgsPHfRhimQwxm2Kkj5zeGEz9O6Fh/4dnmx2X45rM3fa4zdXute3t7iZmLliuv4wmDQ9tUkQaMRNiiJg4OrT3sOldz7Npw6vwLRtT8XwjDmuPALGzX7LF5827gajkssfk7PmO1tTmwstWEm0ooGnT1zPTzfv4eITDx+4zpBIf4zn4is5EJTMqUY5UMa4WCQ1oBnpyB3HNu5Wbqz+VGZe/dBF0NXmfvfig7B0Awaf2NK7CT6Q2pCta9ZXsNUHE1z6S4yNY8KVhGoa+7YR8i1JnHRw7vaENvaREXR8yw/z/3JT/dDeNLmZrExcftzlrM3X5s63D10JH7sUyia7TS67drml6r174eXfufqZ2a/TRBKRETemiz8aY84Hzgdoasoa9Yj1wH2XuMLpXTtTHUDn3O86OkOVriF43yVu9lquhlXP7tTynDxLfg+sdg21gov4ilBA7K47s+8stjnXuAL+oUo3mzO5c2nFFLj7c5k7jAaCuWPaC2V2aCZpyZYUoL+4NZ5h5aMvc8tZ7wd/j6vlloy/FzbC9j+52m7XzYQz78odn3tec7tBJnN0tMvdD5a7GZ9Hnw73XYJ32s1MO6iJbzUVWGdIJrx+c671XYd5eg3ux2+Ak64ehSMVSek3bsHNGtrzmsufu7e5WZXZcXz85X1Xbtx9ocuzn/gPV4P+yPmwej6mvYVgbRP+oluJzP4er+3uocvUcfnq52jt6OXGZTOZUV8DuXLuYAdIVZdtXBswdkXGqH5j10tcX23b4iaTJK/Fymvhns+7x7f/yT2+6TI3eWrztZmdmb+50uXfKe90ZTyqNJFEZKQZa/f/rrLGmA8BV1hrZyfufw3AWvsf+V4zc+ZMu2XLln33/fZteOV10LPTzXyz1v3nR2HDBakOIHBLe+d8P3Pm22k3uVpwHdvd0p0p73Szjo4+PdVYfGoN9qTvYr0gkfAkynp2ug1YvKC7IO/d42aLxnoTjwcgWE7cGqioo607TkXApyry1r7X2eppeLk6ndL48TjxjlZMvBcbKMNUHUBbd3xwxYRzva9v2dkZwfpx6thD0EYxg5i1l3z9cI+jWIpxPAW+x7D+yOzYtbtexnS3ubIIydiNJ5Zj/fpy+NCFLv4S9WLtxc9g2l9xsyFMwM3KCJZBb0eqiHVi6YOtanS/i3S6Ds5YN5RNcp1HJjGLzvrufULl7mLHWjdjyXhgfUzaz/jRxHMr3Bd69859FzN+eT3xzrf2xWmg6gC8np3YWISYCdEVnERNdBfGj2K8oDuueARrAsQDZXjxCMaPgB/HhCqgqhEfw87OCL7vE7dgrSUcDFBXEWJPb5TuSJy4tZSHAhxQVYbnmaLG5WjFeL7PHezjWYoat7s6e5kUsAR6WjHJfPfXR+APt7haxMm6aoEQWFxdoafvgGPOcDkzGHaNu3jExZ0XxHpBjPVTudsLQKAMa313+AaI9kC40m3GFo+453ght8TSj0G8142sB8vdrY0n4tmdWzZQ5uLaj7jaioEQcQwWLyO3GmMIByw18d0E/Sh+IJwz9wLs6YnQ2RvHM5Z69hAiBoEw7d5kIjGbEbv9/ZsB/ebkWMxnR0cv0bhPKODRWF1GMOjh+5bd3b1URtsI2ihesAyTbDT7vqtlN0ZnZY9Kzt29zf1/jfakvsPD1dh4BFMzrZ93KpIx/m8iBSrs33HIsZsdt5Dd1vXcrKC1Z6R979/qBobi7rsU47m2QecOqHs7NhACE8BEOl3sP3ade+MPfxEbrsxsExjP5dVY2nkSKod4DLCurZvMv17APR7vxXpuk0wf8Dta8fwIvhemp6yOnojPJH83QRvF90J0BOvojvqpc9/Goestl9+T3yuhSneM8ajL59a6Nogfd39n2v/79PYygTKs8TCxbnwvjFfdgOcFcuebtH9LO0DuHm3DbZeMRs5N9z8//uxw3npI/uEdmqk5gRS3vbDnDUws4tqWyWs0z8vsWzhmqZsw5cdc/iyvc4NPZTVYcNc8gRBU1EPvbpcrPS+RW+OJNnF54vWJ+3HXFiSRs4n1uFxrjHtOuBqTbAeHKtxrYz3umipUhRftwgSCEI8l2uiJazmMy6uQlmeDUD4Jeva453iB1HeIF0ztyxAsc58d7Xa/CyTa3sbrm4+tDx1vJv4n2kRbPJh4714IVkBVw77rvH35qDKI1/1W5vdq8r2SmzBXTYWeXYNrQ/m+WwUW6078jaHEv8mUkW9/xWOZx59/E+nR/4IZR0ZrpubvgcOMMYcCrwGLgSWDeQO//ADMrucxj3zXLa1Jn+Y973q3u3Qy+XTscJ06SzdAT5tr8Jlg5iYrp93kRrtvW5CxJNhE9mL8GGU97Zis3/HmMzDtyMzl7gubCQbLiXe383rXZN4Tfh2TnJVX2wQLV+E3vjtvx6Yfj+Nvf5bQuiX7XhNbeBs/2+rxk//+274ZozOm1gy6UfPC9r1c+8DzXDUrSCht86NCdqNMvv685i1sa+se8nEUSzGOZ9T+psoGN0v4vq/2jd25K2DyIa7gP8CMOa4D9LHr+z53/k/htJ9DRa3bXXrjv2I6driamq/8D0x7N7T9DaYdBdnnyYw5cNxXUjNGk5/9+A3woc+7L8z1aTGyYCV4r6UGBmbMwRz3FUJpr7cLV8Ej38W8sJHQjDlMOu4rmbG/oBme+QXmXXMIVk91s07SliHbxbfxSuDt/Md9z7P8w4dy6Z1P7/t3ueXsD9DWGeFf1v0x49/qsIZqXmztKMq/4WjFQ77Pzfe3FfNvHoxJAUtg1/N98hnzfpzZub6gGX73PTjoaDjqtD45lWC5i8OOHZgFK12j6BfnZeRvUznFXUAD/O+DcNhsWLc0Mx5DVe7C/e4L3UX98VdkLmtPxLM5/nI3SJCcWVrbRPDUn8BjPyJ23Nf4xoPdbHq2ldlHNLDi+HJC612HQSCRe5O/T/5/rq0M0ro3wo9+8xeumhUknJZLg/ObafHexudve2rAf7Pmcz5Ib8zPm5NjBxzO89s7+ezqJ/e95idL38+Mxmq2tXdR1/EiZek70S9eg/n/7N17nBxlnS/+z1N9mWuSmSSTBAiD4FlhXVZR44qyu4igESKEwGaSQBLCClE5iOxxX+se9cdyeAmvAx4FlQ0QsgqTKxMxghsuSxBhT9ZFw2UxgugRZRIlM0Myk8x9urue3x/frnR1d1Vfq7u6pj/v12tena7pS3X6O0899a3n+T4dZ8hoAa9WG/aYb21uQztw5Dfp7V3XZmDGidLxreT/jdcrQJM/fPoej/d1rdg9fQmw9tHkSVpYpqQf+V1a+4aubuBn9wOv74ay94lH+lMLtj35FajMPsVl98vv0trsLXIytn1leh+7pUOmYSbfQ3dtgQo3I7otNQXe6NqGDba+651d70U0PI6bH30VAyOT6Ln2L3BC/KD0cez7v3SDnHAn4sD31zm37yu3w5x7Bsz+19L6y/bPGu/ahrcaT8OK+59Pb2/mtcAYeO34d6lytN1+9XGPf/9ltpm11ncnqnnRmcCIQ3/h/JuBBz8lCc0PXpOeQ7hipyTPHroSyn6O1nxUXlObyVl66fkCNM6SxOLkMPDIdenPfeqr0mZfei/w+hPAn18mz89oD1VbJ8Jd3cCbzwOnnO18XnfBP0keJO39k+eKJ39QfmdvX5dtlMEEDTOzztVwxU5J1D58ja093iZJw6dvcc/JjPRDr9yON0OnYM13f46Dg+NY/O4O/PMFTTDsbfhVu2Xmlv2Yl3m+mu/Y63S8XrpBBqKNDwGzT6vccTsRB/r2Z8fP/DPdEpvkEV961FrrOIDrATwJ4DUAPVrrXxbzGqGJAenknbXKedrNuV+S+9Yf9b99FdiyTAr4To1IR8n+nIevAY72Zk8JPnoAGH4Lyul3p52baiDs21UIoaO/w3vaJlMd0eTvVc8aKOtKhoPEyADC1h938jnhnivwmQ/OAgAcHBzHtd37cHi0uELrh0encG33Pqz/wMzUau7WPu9YJVesC3j+wcHxsvbDK17sj2+faWJQGjun2H30evn3wX0Su4u/JqMynB67a73UcdlyGbB1uTxnqFde+4xPyt/Baec6v9dZq7KnwD96vWz/4Wdl5IT9d2NvpxKayec7xTbOWuX6e+xcK6P2fnCtXL2yDpLW83dcgZEjh3D5B04+ntAE5Hs5cGT8eELT2nZt9z70j0x69h36FQ9u7+v22bz8zMU43uamtXdrUv+2bneulTj400ucyyyokIzstOLKSmhaj3nkOrniPfa2/LynK5XQtB4z9jZw9M1UDJ1zY1Y8HY/no73pU+WHeiXGz1qFcM8VWP+BmQCA9R+YeTyhaT3O/nvr/zmeAK7b+qJjWzpj11oYY4cL+s7ePDyWs002RwaOJzSt53x2ywvoH5nEyJFDaHvkqoy/n1VyZdhpteE87Xu1+NfmHnGIxTVQiYnK/9+4rQBdI98JFcin7zGr3X19N9B9iYzeMePA0JvZ7VvP2tSx2GpTrTa3Z60cf536FD+41qEfvFra48w2+mhv2nuontUIHf1dzr7r3/X8F46MxvDZj74TBwfHMStxWPrWmfv/yHUyi2r8sHv7nmzvMvvL9s8a7rkCrYnBrPYmMZL9Xbq13X71cS3ltpm11ncnqnkThx37C2g/Re5/5AvZ5/5He1NJPmvbrvXSPkNJv9clX3D84nzmc602+4eflXMn6/lO7WHPWjnvczuvg3J4/+S54vhh5/cf6XM8V3P8rDuuSB0TnHIyyc+idqzCyJFDx9uj9R+Ymd2GZ5ZoczpfzXfsdTpeP3KdnDsMvlHZ4/bIIef4yZH7IW/4ljLWWj8G4LGSX8CMS6A0tacCxzLUC8z5b8C63TJC58e3pEZtNrWnHpP5HGvKS65t9t9Z+5C5XSl5ntvvzbjrx1KJScfnNBmJ43cPDo5jKp5AMabiCRwcHMe8ZpdFk/KsRmk9366U/fCKF/vj22fKF7vaTMWuNnM/1gi5v4Y9RjOf7/Z61vbMuI80F/78XL+39tdl8a62qImxSCTre2mOhhy/q3jC9Ow79Cse3N7X7bN5+ZmLkqu9y9zW1O4em0ql4iQzrqzH2OPPimU76/fW9nzxmCPW5zXL/ru1jdbvAfl/NrXO2Za2Rc20TW7fmRXTbq+jzJjz929qeQ+nz5SIldS+V4vvba7dUK9Mn6r0/w1XgJ4e/Poec8UutHsbarV9mfftbXCp/WBrm327y+My+67N0RCaIVMhG1SisGOAy74q06W9s33WBpXethwcHHftZzu13X71cS3ltpm11ncnqnnWQkF2Vpt7w8sAtHOf1K0ds/rIjudqOdpAe5tt70/nOnd0ex23BZO1mX/fi/msBXwWezvr2P/NfE+3z5vr2Ot2vLaOK5U8brv1wxOxyr0nAfBppKYnrEK+44Nya9fWKQH7w8/J6DL7AiuxMffnxMact1k/mb+z9iFzu9byeLffG+65ZB1qcHzOuBk6fndhexOi4RCKEQ2HsLC9Cf1j2nmf8qxGaT3frpT98IoX++PbZ8obu5MyreHJL8sQ+lyPNRPO25WRHqOZz3d7PWt7ZrzHxgp/fq7fW/urneNwaMrA0Hgs63sZm0o4flfhkOHZd+hXPLi9r9tn8/IzFyVXe5e5bXzQPTa1TsVJZlxZj7G3u1Ys21m/s7bnike390g+p39M9t+tbbR+D8j/s6FUzrZ0aCr9sOr2nVkx7fY62og4f/+Gkvdw+kyhSEnte7X43ubatXUm62BX+P/GWgE6871r5DuhAvn1PeaKXWXkbt+c7tvb4GL6wU7bMt/D4XGZfdexqQSGxuXkblKH8h8DANd91YZLe2f7rJM6vW1Z2N7k2s92arv96uNaym0za63vTlTzcp27W7WEnfqkbu2YteaH47lajjbQ3mbb+9NubbdTX9l6Hdf3z3EMsfa9mM+a79wwo5117P9mvqfba+Y69rodr63jSiWP22798FDu9VSofIFNaiYaO6SG38vbZXq5FUBW3YSffkdu7du7Nst03VkLpSab/XfLNkpB38zXaZ4LzDgBelZnxmt1yyIZXd3Z23UCiVmn4pWhBtlH2+9112boVveFCUKtHYh3bUt7TrxrG+77udTlKHUV9jktUdy/dhE2vnAMhy/O+OwFrEZpPd/qHPm9GrwX++PXZ8oZu13dErtW/OmE1LQqNs5/9YRsf+NZuZ/5/Je3y3b78y65W7Zfeq/Evf13zXOBFVvSnu8U23h5u+vvsbwbeGmr1O0KRbL2W6/chtbZC/DwCwdw++XvSfteTp4t9bgyv6t5rQ2efYd+xYPb+7p9Ni8/czGOx21mrNkP4Nb3/PJ2iU2X9hF770rF1WX3Z8f1zJPkd81zgVd65G8gMx5nnZKKob13Zf8dWPE8K9m+23936b3Ay9sR79qGjS8cAwBsfOEYYsu3ZrW91u+t/+dwCNhw5fsd29LhZd0wm+cU9J2dMqc5Z5tstHbg3tUfSHvOvas/gHmtDWidvQBDSx/M+PvZLsXIV24vun2vFt/b3IzY1aHGyv/fWCtA1+h3QgXy6Xt0bXcjjXKcn3VKdvvW1Z06FlttqtXmdnVLm+3Up7jsfmkv015ri7THmW30rM6099BdW5CYdWrOvuudXe/F7JYI7v3Jb7GwvQlHQ3Okb525/0s3AK3zU31yp/Y92d5l9pftnzXetQ0jofas9ibUmv1durXdfvVxLeW2mbXWdyeqda5tbuNsOacKRbL7trM6ZW2OzLxC2ykAkovmuPWHW+Zlt2/LNqba7EvvlXMn6/lO7WFXtxwP3M7roB3eP3mu2DTH+f1b5zueqzl+1pXbUscEp3PV5GfRK7ejdfaC4+3RxheOZbfh4cb0z+F0vprv2Ot0vLZyOu2nVfa43boge3+7Nst2qihfVj8vhdPKevGJCYQmBtJXPzeM1Kph4cbkytKyYqMON8oITm0iEWpEWE/JcGAjIldgdCK5EmQitVIWAA3l0+rnsiojVz+v3P74tSqkU+xqZcCMNCE0eSy1wiiQXBUvuWiKtVKpEZEYjU/IinJmPLl6dFgW+YlNyL+zVj+3VqTzcvVzidPqrX4ONEYMrn7uZ9weXz1xNpCYAGKjqVUTQ1FZ/MeaVmNvHyPJVczjE6kVFh1WP4d99fP4ROp5Ra1+LjHsvPq5AQ0VmNXP4wkTYa5+XrD8sRsCGmZBNcyozv9NjX8nVCAfVj8HXNrd8beTbarVB42l9UORmEqtvHp8Jd3k75SSPoJSFVr9XFY6n2hox/CEiYSpETIUwoaCUgqxRCVWP58CQtHk6ucTMI0IVz8v7vlc/Rzg6ufBVJ2+7sRh6Us2tkk7lFzJXBthIDoDZmIKRkK2KavtbGwHJoaqv/q5jqf6wVz9nKuf14lAJzWJqqRinT2iCmLcUlAxdimoPE9qElUBk5qVwkRppbG/QEHFpKaHOFSAiIiIiIiIiIiIAsW31c+JiIiIiIiIvPKfbxyu+nvW1OhQIqI6w6QmERERERERUQlcE6kVnH7veSK1gKnyt+5+1dv3LMBXlry76u9JRMESmJqaSqkBAG8W+PC5AN6u4O5UEz+L/97WWn+y1CfXcewWq54/O+D9569m3Dqpxe+T+1QYv/epkrHr92fLxP1xV0v7AhS2PyXHbpltbi38X/m9D3z/0t+/2v0Fv/+vqq3ePi9Qvc/sR183SN8n97UyvNjXsmKX0gUmqVkMpdQ+rfUiv/fDC/ws9aWe/4/q+bMD0+/z1+Ln4T4Vphb3ySu19tm4P+5qaV+A2tsfu1rYN7/3ge/vfwwUKkj76oV6+7zA9P7MQfps3NfKCNK+1gsuFERERERERERERESBwqQmERERERERERERBcp0TWpu9HsHPMTPUl/q+f+onj87MP0+fy1+Hu5TYWpxn7xSa5+N++OulvYFqL39sauFffN7H/j+wRGkffVCvX1eYHp/5iB9Nu5rZQRpX+vCtKypSURERERERERERNPXdB2pSURERERERERERNMUk5pEREREREREREQUKExqEhERERERERERUaAwqUlERERERERERESBEpik5ic/+UkNgD/88eOnLIxd/vj0UxbGLX98/CkLY5c/Pv6UjHHLHx9/ysLY5Y+PP2Vh7PLHxx/yUGCSmm+//bbfu0BUEsYuBRHjloKKsUtBxLiloGLsUlAxdommh8AkNYmIiIiIiIiIiIgAJjWJiIiIiIiIiIgoYMJ+70BZEnFg5BCQiAGhCNC6AAgF+yNRnWDsUhAxbimoGLsUVIxdCiLGLRERVUlwjy6JONC3H+hZAwz1Am2dQNdmYP6ZPGhSbWPsUhAxbimoGLsUVIxdCiLGLRERVVFwp5+PHEodLAG57Vkj24lqGWOXgohxS0HF2KWgYuxSEDFuiYioioKb1EzEUgdLy1CvbCeqZYxdCiLGLQUVY5eCirFLQcS4JSKiKgpuUjMUkekMdm2dsp2oljF2KYgYtxRUjF0KKsYuBRHjloiIqii4hU1aF0h9lsx6La0L/N4zotwYuxREjFsKKsYuBRVjl4KIcUvTwK27Xy37Nb6y5N0e7AkR5RPcpGYoLAWnr36cK+tRsDB2KYgYtxRUjF0KKsYuBRHjloiIqijYR5dQGJi10O+9ICoeY5eCiHFLQcXYpaBi7FIQMW6JiKhKgltTk4iIiIiIiIiIiOoSk5pEREREREREREQUKL4lNZVSbUqp7yulfqWUek0p9WG/9oWIiIiIiIiIiIiCw8+amt8C8ITW+m+UUlEAzT7uCxEREREREREREQWEL0lNpdQsAH8NYB0AaK2nAEz5sS9EUlrO1gAAIABJREFUREREREREREQULH5NPz8VwACA7ymlXlJKbVJKtWQ+SCm1Xim1Tym1b2BgoPp7SVQixi4FEeOWgoqxS0HEuKWgYuxSUDF2iaYfv5KaYQDvB3CP1vp9AEYB/GPmg7TWG7XWi7TWizo6Oqq9j0QlY+xSEDFuKagYuxREjFsKKsYuBRVjl2j68SupeRDAQa3188n734ckOYmIiIiIiIiIiIhy8iWpqbU+BOCAUur05KbzAbzqx74QERERERERERFRsPi5+vnnAWxNrnz+BoCrfdwXIiIiIiIiIiIiCgjfkppa65cBLPLr/YmIiIiIiIiIiCiY/KqpSURERERERERERFQSJjWJiIiIiIiIiIgoUJjUJCIiIiIiIiIiokBhUpOIiIiIiIiIiIgChUlNIiIiIiIiIiIiChQmNYmIiIiIiIiIiChQmNQkIiIiIiIiIiKiQGFSk4iIiIiIiIiIiAKFSU0iIiIiIiIiIiIKFCY1iYiIiIiIiIiIKFCY1CQiIiIiIiIiIqJACfu9A+QD0wTGBoD4FBCOAs0dgMH8dlXxO6AgYtxSUDF2KagYuxREjFsiIqoSJjXrjWkC/a8CO1YBQ71AWyewcjsw793sbFQLvwMKIsYtBRVjl4KKsUtBxLglIqIq8i2pqZT6PYBhAAkAca31oqJfhFcBizc2kOpkAHK7YxVwzR6gdb6/+1YvxgaAZ24DFt8GNLUD44Ny/+I7+R1Q7WLcUlAxdimoGLsURIxbIiKqIr9Hap6ntX67pGeaJnDkDWDwDSDSDMTGgPbTgNmnMbGZS3wqldC0DPXKdqoO0wT+6ovA+GG5H26Q+6bp734R5cK4paBi7FJQMXYpiBi3RERURX4nNUs3fgQYfgvY/cXU1IalG4CmNqBlrt97V7vCUfm/sic22zplO1WHUpKEz4xdpfzeMyJ3jFsKKsYuBRVjl4KIcUtERFXk55BGDeDflFIvKKXWF/3s2DjwyHXp06gfuU62k7vmDqlr09Yp9606N80d/u5XPUnEnGM3EfN3v4hyYdxSUDF2KagYuxREjFsiIqoiP0dq/qXW+g9KqXkAnlJK/Upr/Zz9Aclk53oA6OzsTH+2TgCt89Lrtey9S7aTO8OQQt3X7GEt0grKG7tOJQC8iF3WmaUyVDxuGZ9UIewvUBDljFugsv2FTGyfqQi+9XMtjFcqUd52l4gCx7ekptb6D8nbfqXULgB/AeC5jMdsBLARABYtWqTTXiDaCnz8a8Cu9ampDcs2ynbKzTBYqLvCcsZuuMmlBEBTeW+aiMtqkw9dydUmqSQVjVuuhkoVxP4CBVHOuAUq11/IxP4DFcmXfq6F8UplyNvuElHg+NLyK6ValFIzrH8D+ASA/UW9iBkH/uM7MvJi3W65/Y/vyHaiWtbiUgKgpYwSAKYJjBySn0vvAVZskZFJO1bJlWyicpUbt6O21VCtNvuZ22Q7USWxv0BBVYn+Qib2H8hrlYxbxisREWXwa6TmfAC7lBSMDgPYprV+oqhXMBPAhz4DPHp96irdJXfLdqJaVokSAONHJDlkL8p+yd3Aj2/hyvbkjXLj1oy7tNlMLFGFsb9AQVWNkkHsP5DXKhm3jFciIsrgS1JTa/0GgPeW9yJm6gQFkNtHrwfWPVb+DhJVmtclAGLjQM/a7L+HJd/gyvbknXLilm02+YWxR0FW6ZJB7D9QJVQqbhmvRESUIbiFR6pZPJ2o1rn9Pcx+J1e2p9rANpv8wtgjcsf+AwUJ45WIiDKUnNRUSr2olPqqUuqdXu5Qwawi1HaVKJ5OFARufw/RFhZNp9rANpv8wtgjcsf+AwUJ45WIiDKU0/q3A2gD8IxS6mdKqb9TSp3o0X7lV43i6URB4fr3MM/f/SKysM0mvzD2iNyx/0BBwnglIqIM5dTUHNRa/z2Av1dK/RWAVQBeVEq9BmC71nqjJ3vophrF04mCgn8PVOsYo+QXxh6RO/59UJAwXomIKIMnCwVprf8dwL8rpT4P4OMAVgCobFITqHzxdKIg4d8D1TrGKPmFsUfkjn8fFCSMVyIisiknqfnrzA1a6wSAJ5I/lWeawNgAr9RR8DB2KYgYtxRUjF2qR4x78gtjj4iIqqTkpKbWemUhj1NKXaW1frDU93FlmkD/q8COVbLqnVVTZd67edCk2sbYpSBi3FJQMXapHjHuyS+MPSIiqqJqHFm+UJFXHRtIHSwBud2xSrYT1TLGLgUR45aCirFL9YhxT35h7BERURVVI6mpKvKq8anUwdIy1CvbiWoZY5eCiHFLQcXYpXrEuCe/MPaIiKiKqpHU1BV51XBUpjPYtXXKdqJaxtilIGLcUlAxdqkeMe7JL4w9IiKqouCO1GzuAFZuSx002zrlfnNHRd6OyDOMXQoixi0FFWOXgiwRB44eBI78Tm4T8cKe19whdQzT4n47454qj20uERFVUTmrnxdqb0VeVZuAEQGWfAOINAOxMbmvTVQnV0tUIsYuBRHjloKKsUtBlYgDffuBnjWpBVe6NgPzzwRCebrwhiELs1yzhytQU3WxzSUioioqOamplPofuX6vtf5m8vb6Ut8jp5FDwLbl6TVb2jqBqx8HZi2syFsSeYKxS0HEuKWgYuxSUI0cSiU0AbntWVN47BoG0Dq/svtIlIltLhERVVE5IzVnJG9PB/BBAI8m718M4Gfl7FRBEjHnItSJWMXfmqgsjF0KIsYtBRVjl4KKsUtBxLglIqIqKnkOgNb6f2mt/xeAhQDer7X+otb6iwA+AKAz97OFUiqklHpJKfWvRe9AKOJchDoUKfqliKqKsUtBxLiloGLsUlAxdimIGLdERFRFXhQ2mQ9gynZ/KrmtEF8A8FpJ79q6QOoK2YtQd22W7dVgmsBIHzB0QG5NszrvS8Hnd+wSlYJxS0HF2KWgqlTssg9LlcQ2l4iIqsiLhYK6AfxMKbUref9SAA/ke5JSaiGAJQBuBZCzPqejUFgKpV/9uExnCEXkYJmvcLoXTBPofxXYsSpVuH3ldinIzgLslI8ygKbZwJUPA0oBWgPhRtlOVKsYtxRUjF0Kqkr0ddmHpUpjm0tERFVUVgZQKaUgSc3HAfxVcvPVWuuXCnj6XQD+AananE6vvx7AegDo7HSY0R4K+1Nwemwg1RkE5HbHKllhkgXZCXlid2wAeHBJdgF1xg/5jHFLQcXYpSDK288FvO/rsg9LHmCbS0FVULtLRIFS1iUzrbUG8JjW+kWt9beSP3kTmkqpTwHo11q/kOf1N2qtF2mtF3V0dJSzq96KTzkXwI5POT+e6k7O2GX8UI1i3FJQMXYpiHzp5/LvgTzANpeCqmbzC0RUMi/mAbyolPpgkc85B8AlSqnfA9gB4GNKqS3FvrFpagwMT+IPg2MYGJ6EaepiX6I04ahzAexwtDrvT8HG+KEgYtxSUDF2KcA87+vy74EqjTFGRERV5EVS80MAfqqU+q1S6hWl1C+UUq/keoLW+n9qrRdqrd8BYCWAH2utVxfzpqap8XrfMJZt2Itzbn8Gyzbsxet9w9VJbDZ3SP0hewHsldtlO1EeZtNcxLu2pcVPvGsbzKa5/u4YUQ6MWwoqxi4FVUX6uuzDUoWxzSUiomryYlWdxR68RtEOj07h2u59ODg4DgA4ODiOa7v3Ydd156BjRkNl39wwpKD6NXtkKkU4Kp1BFlinAhwei+Ore8ax/uM7Ma9ZoX9MY+OeY/jasjg6ZoT83j0iR4xbCirGLgVVRfq67MNShbHNJSKiaio7qam1flMp9V6kFgr6d631fxXx/J8A+Emx7zsVTxzv5FkODo5jKp4o9qVKYxgsdk0lmYon8OSrA3jy1YG07TddXKXYJSoB45aCirFLQVWxvi77sFRBbHOJiKiayr4sq5T6AoCtAOYlf7YopT5f7uvmEw2HsLC9KW3bwvYmRMO8Aki1jbFLQcS4paBi7FJQMXYpiBi3RERUTV7MNfk0gA9prW/SWt8E4GwA13rwujnNaYni/rWLjh80F7Y34f61izCnhUWoqbYxdimIGLcUVIxdCirGLgUR45aIiKrJi5qaCoB9PkEiua2iDEPh9I5mPPeZd0GZMWgjArQ2wzAq/tZEZTEMhdPnteCZz74bKjEJHWpAqLWl/mLXNIGxAdb0Cgi2uRRUjF0KKsYuBRHjloiIqsmLpOb3ADyvlNqVvH8pgH/x4HVzS8Rh9O8HetYAQ71QbZ1A12Zg/plAyIuPRVQhpglj4DUYO1YBQ72plUfnvbt+knqmCfS/CtTz/0HQsM2loGLsUlAxdimIGLdERFRFJWcPlFJnKaWU1vqbAK4GcCT5c7XW+i6vdtDVyKHjB0sActuzRrYT1bKxgVQyD5DbHatke70Y7ef/QdBUus01TWCkDxg6ILem6c3rErG/QEHF2KUgYtwSEVEVlXO5bBOA05RSLwD4DwB7AfxUaz3syZ7lk4gBrfOAxbcBTe3A+CCw9y7ZTlTL4lPOsRuf8nvPqiMRB6ZGU51dy1Bv/fwfBFEi5vydedHmVnrkLksd1Df2FyioGLsURIxbIiKqopKTmlrrRUqpZgB/AeAjAG4AsFkpdQjAXq31dR7to7NwI3D+zcAj16VOgpdukO1EtSzS5By7kaa8T50WRg4BR34rn9ueJGvrlIQT1SYj7PydGR5MJXMbvXzNHqB1fnmvzVIHxP4CBRVjl4KIcUtERFVU1hmd1npMa/0TAN8CcCeAfwbQAuCT5e9avjdPpA6WgNw+cp1sJ6plpkvsmtM8dq3pxYkY8OztwCV3S0cXkNsVW2QEHdWmcAOwvDv9O1veLdvLFZ+q3MjdUZZ7qHvsL1BQMXYpiBi3RERURSUPsVFKXQEZoXkWgEkAPwfwPIC/1FpXvmiKGXc+CTbjFX9rorIkXBI4iWk89do+Wu6KncBIP/DjW1JTk2JjMiKPI+dql9bA/h/I92eEJAn/0lbgI9eX/9rhaGVG7pomMDXCUgf1jv0FCirGLgUR45aIiKqonAzCfQDOBvAAgM9prf9Ra72rKglNAFCh1IghS1unbCeqZUq5xK7yZ3+qwT69+KffkRF+I/3AQ6uBH34OaJkHNM/1ey8pFyMEvOsTwLblwN2L5PZdn5Dt5WrukCnh9lGgK7eXP3J3bCBV6sCOpQ7qC/sLFFSMXQoixi0REVVROUnNNgDrATQCuFkp9YJS6l+VUl9RSn3Mm93LQans6auX3D29E0M0PaiQS+xO486efXrxS1uAfZtkxN8NLwNXPw7MPxMIeVCbkSonNg48fbOMrl23W26fvlm2l8swpMblNXuAG/fLrRc1L+NTLqUOtrLUQT1hf4GCirFLQcS4JSKiKipnoaAEgBeTP3crpeYDWA7gRgC3AKh8hub5+9JX1nv+PuCiOyr+tkRlMQzn2L34Tr/3rHIypxe/tAX43XPeLARD1RGOpkbXWrwc8WgY3seCtc+ZpQ5mnshSB/WG/QUKKsYuBRHjloiIqqScmprvgdTUtH6iAP4DwHcA7PVk73JpXQAsvlUWHVFKpq8uvlW2E9Wy5g7g47cAg2/I/XCD3J9uI8dMU6b/xqeAUBRYvQvYsix9Berp9pmns+YO4KrdQHxC2lytZSXTWv4OrWntO1ZJMtaKu6bZfu8ZVRP7CxRUrQuA828CjiYvCIYb5L4fsWs/poej0r7y4hA5qaW4rTb+nRARVV058z0fAPB/ATwO4Kta697cD09RSjUCeA5AQ3Ifvq+1/qei92DiKNCzJpUk6doMzDq56Jchqrr4BLD7i+kJvunEvjCQ/TNe+4xMV2ZHL3i0CYwfyW5zZ56I8iqZVJB9WjtPMOob+wsURMoAzFhGf2GbbK8mt2O6F2VCaPqplbitNv6dEBH5ouQWVmv9fq31DVrr7bkSmkqphx02TwL4mNb6vZDV0z+plDq7qB0YOZQ6QQHktmeNbCeqZfZFcwC53bFKtk8Xbp9RJ4C2k7nSeRAFtc21prUz7upXUGOXaGwA2HFFxrH0iur3F+qh30LeqZW4rTb+nRAR+aIaK3OclrlBa60BjCTvRpI/uqhXTcRSBw3LUK9sJ6pl9kVzLEO9sn26qIfPWG/Y5lJQMXYpqIo9llZq6iuP6VSMeo2Xev3cREQ+q8aQFcdkpVIqpJR6GUA/gKe01s8X9aqhSGpVPUtbp2wnqmWhqEvserTgSi0Iu3xGrxaVoepjm0tBxdiloCrmWGpNfd10AXDXmXLb/6psr+Z+ENVDP9cJ/06IiHxRjZGajpKrp5+llGoDsEspdabWer/9MUqp9QDWA0BnZ8ZBItIMdHUDPWttNbK6ZTuRz3LGrhEClm4AHrkuFbtLN8j2YtRaMXL7/kSaUgu0cGGgwGCbS0HF2KUgyhm3QPpiZ/mOpW5TX6/ZI6U37IrtPxSzH1QX8vZzL98EPHxNKl4u31R8Pzdo+HcSCHnb3aTze79d/ps9Oae4xy++tfz3JKpDSmaCV/ANlHpJa/2+PI+5CcCY1vr/uD1m0aJFet++fakNI/3A1GhqNVOtZdRFtAVonefZ/hMBUOU8OSt2hw4A318HnHMj0NQOjA8Ce+8C/uYBqfvnJnM18cnh7NXE/SpG7lQcffUuoGEGkKiRpGv98TZua7nNrbUEP5WrfmKXppuSYzcrbgFp2468AQy+IUn42BjQfhow+7TsNm7ogIzQzHTj/vS+RamLmbCdnc68b3PHjsjq51bczuoEmmdP/zaXfyfV5m3s2vznPZ8t56UBAGefxqQmuSordildySM1lVJPa63PV0rdrrX+Uo6HZv1OKdUBIKa1HlJKNQH4OIDbi9qBxBTQfUl67ZK2TuDqx+XfPKhQrQpHpcP30OrUtnzTU5xOQpZukM7hUG/uERnV4DRCZMsy2Z9ciVoKjvikc5u77jH/9gngaqOUX77+AlGtGh1IXby0tHUCn94DzMg41ltTXzMfm9m3KHREp1M/2o/+BQVPYgrYtrywNne6na9ZixMSEVHVlHPUOEEp9REAlyil3qeUer/9x3qQ1vrfnJ4L4Bml1CsAfg6pqfmvRb17rsL/lawrRFQua3qKVXenkOkpTichj1wnoz0tfhYjZ3H06c+MO3/HZtyf/bFwtVHKhwsFUVDFx12OrePZjy20b1HI8Zr9aCpHoW0u44yIiDxQTk3NmwD8fwAWAvhmxu80gI+5PVFr/QqAnFPS8zJCzlekjVBxdYWIqs0wZBTZNXsKvzLtdhLS1J6639YpUyv9UOgIEQouI+zS5vpWmlkwoU755OovENUy5RK7yiF2C+1bFHK8Zj+aylFom8s4IyIiD5Q8UlNr/X2t9YUA7tBan5fx45rQ9EykWabf2q9IL90g23mSS9ON24qKsbHUvy+52/lEpxpKGX1KwRJuAJZ3p3/Hy7tlu6/7xdVGKQ8j6txfMBgjVOMiTS593Sbnx1tTX9tOlluni6WFHK/Zj6Zy5DpHs2OcERGRB8oaYqOUigL4g1LKWuDnlwC2aa0ny96zfBrbgFkLgSsfTi/839gG6ARHjVHtKqbwv8VpRcVlGwEzBqzbLYsNPX8fcPGd1f0c9jpIHWcUN/qUgkVroPd54KofAdoElAH86gngzGXFv5aXNbS42ijlEwoDMxak9xeUku1EtaxpNtB2Snrshhtle6nyjeg0TXmvK3dKH8VazHCkn/1oKkyuczQ7zvIhIiIPlLNQ0LsBPApgL4AXkps/CuArSqmlWutflr97OUwek4UrMlfWmzzGk1yqbeNHJE7tJo/J9pa5zs/JPAlxW/28WjHOxVnqTygCvPOjwNu/TrW57/yobC+G17FTSjkHqi9GWOLu6Ju2/sIp/pdOICpEYgoY+n36RdBy5VrMZPyIrKS++4sZCxPOZz+aCpPzHM2WkOf5GhEReaCcHv13AHxOa/2UfaNS6gIAdwM4r5wdyys+KatCZna6GmfxJJdqWyIGTI1mx26+RSsyT0JaOvyLcdZBqj+52txiVCJ2uNoo5RIbB0b7HWJ3JtDUlv/5RH4ZPwIMv5Udu01t7hdByxUbB3atz16YcN3j7EdTYQrtL/B8jYiIPFDOUeOkzIQmAGit9wBYUMbrFsaMSScrs9NlJhNDhdQVIvJDvtgtlJ8xzjpI9ceruGXsULV5FbtE1RYbd47dmMPq514wTQAauPQeYMUWYOGi1PvqeGXek6afYtpcnq8REVGZyhmpaSilGjLrZyqlGst83cJo0/nEWJsVf2uiskyH2GUdpPrjVdwydqjapkObS/VJJ1xiN+H9ezmVBrnkbuDHtyTrabosTkSUiW0uERFVUTmXw7oBPKyUOsXaoJR6B4AeAJvL260CGGHnFW9ZI4tqXVBj1zSBkT6ptaVCXO283hQbt/Z4GelLjgBCYSvvEnkpqG0uUbjJOXYrkWB0Kg3y6PXAuV+SNrqFbTQViG0uERFVUclJTa311wA8AeDflVJvK6XeBvAsgKe01rd4tYOuVEiuINtPjC+5W7YT1bIgxq41gmPTBcBdZwL3nycrsH56D3DjfqmHxEWCprdi4jYzXjZdIPdNM72GFmOHqiGIbS4RADTPkWng9thdsUW2e82tNMjcd7GNpuKwzSUioioq65KZ1vpuAHcrpWYk7w9nPkYpdZXW+sFy3sf5zRPA8/cBi28DmtqB8UG5f9Ednr8VkaeU4Ry7n7rT7z1zN+owgmPLMklItZ3s775RdRQTt26LAX16D6CQWhBg5kk8UabKY3+Bgmr8MPCT29Nj9ye3AxffmXtxNNOUdrjQxVdMEzDjzqVBIk1sp6k41Whzi41xIiKatjyZB+CUzLT5AgDvk5pQwIc+I1Nj7LV/oLx7Cx4wqRKMEHD251JF1K1VIY0avYJtmsDUCBd3qXfFxK3biJ+pEWDzpannr9zOEUBUBVXoLxBVQnwKeH23/NhdeHvq35l91aY5wMCv0mtj5mtrxwaAJ78ifxf2v5MVW1kahEpQZpub7/zLqf4r+xNERHWrGsVNKnPWoBPAb/YAV+yUk2ozAby0FZh9avGv5XTwBHjApMqIjQODvwfW7Za4NULAG88C7e8o73UrlYQfGwCO/JaLu9S72DjQ+1Pgqh9JsX9lAK/0OMdtyGUxoCO/zR69ec2e3COOLLzIRKXSCaDvtfTY/dUTpfUXiKop38JqTsmdTz8lbfDqH0gf46ffyd/WWsnT0b700XUtbGepBNp0aXNPy//cQhKWbrNBCu1PEBHRtFKNpKauyKtGWoA/vxzYtjx10OvaLNuL4XbwnLGAB0yqjGgLsODPgQeWpMdutMjYtavEVWsriTQ1Bjx7O0dw1LtoC/AnHwcevNgWt93OcWuEZBSnfVRnVzfw2N+nP67Q0b6JuMT3Q1fyIhMVLzoDOOXsjNjdLNuJalnjbInVnjXpsds4W36fmdw59a+B4UPpj1/eLb9za2tNE1BKHntwH/DQatne1il9XqJiNc50bnMbZ+Z/biEJS7fZIOXOHgraxdOg7S8RUYVUo+WrzEjN2Fiq0wbIbc8a2V4Mt4NnbJzTbakypkadY3dqtPTXdIvjsYHSXi8RB4beBI78DohPAi3zgR/fIiM41u0GlnwDmHkiO0/1ZGoU6FmbEbdrneM2Ng48fXMqXhbfBkwOAyP96Y8rZLSvaQJHD6QSmtZ7lxPfVF+mRlza3BF/94son9E+4Nk70tvSZ++Q7UB2cufDn8+O9Z1rgY98wbmtNU3gyBsye2T1D4ArdwILF6UuHNX6hUvTBEb6gKEDcmuafu8RAcDEMec2d+JY/ucWkrC0RjDblTt7KNcCh7UoaPtLRFRB1RipuTdzg1LqZADdAOZDRnJu1Fp/q6hXNePOBz0zXtzeuR08dYLTbakyvIpdOy+vWlsdJfuouOXdwHNflxEc1slO0+zS95eCp5i4DUclgWmN+AGA05fI6N7M0Zb5TprHBpInrbzIRCWqRJtLVA2JmHNNzcW3ym3m9HQj5BzrobBzWzt+BBh+K3tU/YwTgJZ5tX3hknUVa1c5bW6+kguAxPLK7dnffTlJ+KBNaQ/a/hIRVVDZSU2l1P/I9Xut9fUOm+MAvqi1fjG5cvoLSqmntNavFvzGRsj5oFfsYiuuB88m7w+YRIB3sWtXSCewUGMD2aPidq6V+rWLbwWizZziUo+KiVunE47zvgx0nCEd7mKmSsWngNEBXmSi0lWizSWqhnyxm9nWau38+FDUua2NjacSmkBqBP66x2r/GM+kTu0ywi5xW8BpZyEJS8OQ5HWx/YlcKjWlvVKCtr9ERBXkRY9lEYDPATgp+fNZAO8HMCP5k0Vr/ZbW+sXkv4cBvJZ8buGUAVx6b2r6QVun3FdFfCTTBFRIRg/ZX2fldimObh0wb9wvt7z6S14INchICHvMdXXL9lJZncDMOC4lCe/WUZoYkoRm63z+HdSjYtpc+wmHvf0MhSV+2k4uLI6O13o7BVj+YPp7s6YrFSoUdWlzmRSnGhdpco7dSJPcz2xrZ8yX2oVpj98MtC7Ifm3TdB9RpxOV+0xeYVKndoUiLm1uJP9z3foPmf0FwyiuP5FPJaa0V1LQ9peIqIK8mH6+EMD7k8lJKKVuBrBba70657OSlFLvAPA+AM8X9a5GGGholdp+kWappdnQWthVQCB92krrPHmd2e8Eoq3pqz3yai95zTAkZq98WBI2WgPQ5XXIvLxq7Tbqs3U+k0j1rNg21zrhKFXm1MLTl0jNt8lhWZl31slMrlPhnNpcolrX2A5MjqTHbigi2y1WW5uIA337gV88LDMrjLAcz1sXyAUlO6uWpjaBv31SRsPvvUsWCrJmK9U6L2eokPfKaXPL7T+UohJT2ispaPtLRFRBXiQ15wOwXxadSm7LSynVCuBhADdqrbOqRyul1gNYDwCdnRlXo7Qp9doyOzN/+2Rhe22ftjLUC2xdnlrpkSfKVKacsRufArb+TXbsXv1E8W9UiZUPnTpKK7YyiVQHKtrmFitzauES/vw2AAAgAElEQVTru4G+XwBXPw7M4CJVlC5n7JoJ79pcIg/ljFtAkpGzTgZGDkl9zVDEOUkJyGOsxVl++m3Z1tYpbeashemPnRgCJo8BO69KHecvuRt4/j4pFdISgMQIkzq+mnZtbiWmtFdS0Pa3huRtd4kocLxIanYD+JlSalfy/qUAHsz3JKVUBJLQ3Kq1/oHTY7TWGwFsBIBFixalX+KLT8oIy8W3yaid8UG5yhyfLGyvOW2FKihn7CamnGM3UWTsVapIPjtKdStvm+vYZuZpc0tNvLsu4lbmqGaalqrS5hJ5LGfcWkLh7KSkk0TMuc1MxNK3mSYwcTSV0LQe9+j1ssL6zIXpbWwlLp56gX0VX03LNtePEaLlCNr+1oiC2l0iCpSyk5pa61uVUo8D+Kvkpqu11i/leo5SSgH4FwCvaa2/WdIbhxuB829OX7Fx6QbZXtDzy5i2kogXdtWcyEm5sWupZJF8dpQoUymLrZSTeOfUQvKKV20ukR/iMelzmnGZUt66AAg71CYMRVwWCcp47NgAMNLnsjp1IjuhWcsrjLOvUpvY5hIRURV51SNpBnBMa/0tAAeVUqfmefw5ANYA+JhS6uXkz0VFvaOZyF6x8ZHrZHtBe1ziwipWzaLvXQh8+yy57dsv24kKoV1it9jC/BxtTNVkROSkxN5mLt0g2924Jd7HBvK/n5eLX1F9K7e/QOSXeAy6/5fAAxdJn/OBi+R+PJb92NYFhS0SFJ+SGppOi4xkLp5VThtO9YttLhERVVHZwwuVUv8EWQH9dADfAxABsAWSuHSktf6/AFQ576t1HMohoaN1vLAXLnXair1mUfI90bPGuWYRkQOdcIlds8DYtXAkG1WRBqCiLekLBUVbZLvbk8pJvHNqIXlEm2X2F4h8okcOQWX0OVXPGuh1j0G1nZz+4FAYmH+m9EdzzSQKR4GXt0sNzUevt9XO3pI96pEXT6kEbHOJiKiavJgzvQyyevmLAKC1/qNSaoYHr5ubCjsndFQRH6mUaSuF1iwicmMYLrFbZLKm3CL5tVoni2qTTiRXMLVv07lHGBebeHeKSU4tpHK5lU5QOUonENUCM+4yTdxldlAh9TebO2QxoGduk5qHLcl2duZC5wQoL55SsdjmEhFRFXmRwZjSWmvIQB4opVo8eM284uEmx2k28XBTZd7QNKUGEQBcuRNYuCj1O6eaRURujAiwbGN67C7bmHsar+Pr2Eay3bhfbgutc2XVydp0AXDXmXLb/6psJ3KiNfDLHwKzOuUEeFan3M9MdNoVM4WcMUmVYkSAyzelx+Hlm4pvc4mqzYg4TxPPjF2rjzp0QG5ztZtW3+HiO4ETzgJmnwq0neJcp5NlQKgUbHOJiKiKvBip2aOUug9Am1LqWgB/C+B+D143t0QMePaO9JX1nr0DuKi0dYdyciqUvnQD8PTNwEi/c80iIhcT0XY0Nh2Fsk3j1U3tmIi2o+iUfKlF8iu5yBBNSxONHWj888uhti0/3g7qrs2YaOxwj9tippAzJqlCEqEowg2z0ksnNMyS7X7vHFEOiVADwks3ZC24kgg1pGK3lMV8Cu07sAwIlYBtLhERVVNZx5bkKuYPATgDwDFIXc2btNZPebBvOYV1DHh9t/zYt194e3EvVMgUXKeT7UeuA9btlinDXP2citAYO5pKDCWptk40fnoP0FillSG9rJPFaex1oTF21LG2W1rcusVCISfPrN1GFRKKjQJP3wKctUpOsOOTwNO3IHTh7QBm+717RK5CiQm5gG6/gP/0zQj9zQOpB1X6glAtrTDO/kYghGKjQEY/F22dCK17DI5tLr9XIiIqQ1mZOK21Vko9prX+cwAVT2TaKZc6P6qYOj+FXt12O9mG4uJAVDSVcI4nlahi8sarOlmljBChQMobt+XGAmu3UYUoZQAf+kz6oiiX3C3biWqYCkdlRtBDq1MbM/u69XJBiP2NwFA64dxfcKrBze+ViIjK5MXR4kWl1Ac9eJ3iNHcAq3dJfct1u+V29a7i6vy4Xd0eG0h/nHWybceTbSqVX/Fkr7mlIX8v5dbJKvRviIIvX9y6xcKxP+Sv8QawdhtVkE4lNAG5ffR6JEuBE9WuQvq69dJHZX8jOMJNLjHpUKyG3ysREZXJiznTHwKwWin1ewCjABRkEOd7PHjt3OITwO4vpl/ZK+r5ea5uJ+LAyCG5Xfso8ORXZLo7T7apHOWsWl7qFB23K+HXPgPExkuf7lMvI0Qof9y6xcLQm8APP1dYjbdctds4PY1KpU2gdV76FN69d8l2oqArp09RqFpof9nfCI7mObLegFWyJrmYK5rnZD+2Et/r8fO3mCzkyjJhRETTWsktvFKqU2vdC2Cxh/tTOC9qCOWa7hiPAccOygij0QHg5e3AR78kRa8NgyfUVJ6GmcCVDwNKyerR4QJqaZYzRSfX30vbyaV/Dk4Zri/hxvTC//a4tcfCwkXAOTcCLR1AY5sklAppn91qt3F6GpUjFAUu/Dow9rbcDzfI/RDbKapx40eA4bfSL+Av3QA0tQEtc+Uxlb4gVCvtL/sbwTF+2Hkx14vvzD7GO32vpy+R/vHQgeJjNhEH+vZnJ1Tnn8nEJhHRNFVOb+SHAKC1fhPAN7XWb9p/vNm9HLy4suc23bFpDjDwGtB9CfDdxcCTX5Z6XD+5HdAJOSDbD66mCQz3AYO/lwPw6Nv5p1pS/Ro/Aoy8BWy9HLh7kdyOvCXbc9CjZUzRqdQIB04Zrh9jA8BTN8kiK4DcPnVTKv6sWDh9CfCxm6Td/O5iWSzgYzdJYjMz3hJx4OhB4Mjv5DYRd39vTk+jUmkNTI1KYuiBJXI7NSrbiWpZbDy18jmQWqgyNp7+OOuCUNvJaX1UMx6H7tsPbLoAuOtMue1/Nb2Pmq8drpX2l/2N4IhPycy2h1ZLm/vQarnv1OfM/F5PXwKc+w/A9y50j9lcRg6lEpqA3Paske1ERDQtlXPJStn+fVq5O1IsHYpCOVyx1aFo2o7l5HZ1e2wAeOjK7Ppbi2+TqQx2Tlewl24AZpwAzD6No4goW3wCePia9Ph6+Brg6sddn2ImElBTo0UnJk1T4/DoFGYijIZKjHDIN0KEpg1tmlAOi61o05Q214qFi+6Qk5HM9nPJN9LjrZjRFJx2SGXQZgzKITGk1+0uvL9A5AeXBVfgtOBKBjORgDp2ACqzP2sfNV9IO+zW/lp1uqt17Gd/IzB0KOJyjhbJbnMzv1elsvsQxczES8Sc4zXz/I2IiKaNcnoC2uXfVZEwIsAVO9OLp1+xU7YXw+nqtlsHrqVDarPYOV3BfuQ6YPANjiIiZyV0uMyxI1DaLGoxANPUeL1vGMs27MXKrf8PQ0sfrMwIB5cRIjS9aDMBPH+fXNxZt1tun79PtlsMQ+oUOsX37Hemx1sxoynqZSEMqgzTJTFk5k8MEflJuyy4op0WXMlgTg5LAinXBaFC2mGn9vf0JVKaKdcI0EpgfyMYtJYBHvY+59IN7qPjre915kkyC6TYi5j20cZGWOLTrq0z+/yNiIimjXJ6A+9VSh1TSg0DeE/y38eUUsNKqWNe7aCbkI6nFgqyppPFJxAq4Op1Tta0G6cT6Nb5Umzazi0BGmnmKCJyFoo4x1eODlcoMS5TfS+5O62TqFdscU5MmiYSw31omzqEb33qRADA1Y+N4hcX/gCJL/xCrnizHiEVwVSGlOF48svS5ibLcpgqlHpQIi6JIscEZGMq3hJxSX5eeg+wYovU4ATck/ucdkjlCLkkxVlTk2rckDELE5dvSWv7Ji7fgiFjVu4nxmMIDf0eOPyb3BeE3C6yAjIKc+iADFtYvSu9/V18a/aMJpYEIUt8Anhlhww+uX6f3L6yQ7bnMjYAHPltcRcxrdHG37sQ+PZZwAMXyfR1K7FpjT7OPH8jIqJpo+Tp51rrUP5HVVB8wvnq8rrdpb+mdWB89g5JHtmnWa7YCsxcmD0t0q1weWyMo4jIkVZhqKUbUnWyklewtQq7T4U0TalHNNqXXni9eW52YjJZEiGyYxVOGOrFCW2d2HTxg7jmiVFc/L1fY++XzsNJrc2V/pg0zRjaTLWJwPFp5cY6W9mEkUPAk1/Jbj+7tgDKltDs/6XU2LJ+f+m9wJ6bgJF+5+Q+px1SOVRIRglltLlQ/nZjiPLRpka4ZVbawoLhUBTazDNBauQQVM8aqWWc0R7rFVuhrAtC1kXWzEVaxo6kkpbWRaRrn5FanuEoS4JQbuFG4KzVUlPbiqFlG/MvihmfAp693fkczO0iptto43WPSfKdq58TEU17wW3hKzGdzH5gtJJHLR0yHWLmSc4n0NYIIqeamhxFRE7i48DTN6cnJ5++Gbhsk/tzIskpaAf3STIIkPuf3pP9WIeSCHN+dBW++vGd+MK/xhAN80SeiqdNU06Q7XG79y5obV9wIuacfG9qT7WfI32phCYgtz/8rIzajLa6j6ZwWxmdKJ9S2lyiGjBDDyN89EBaQj68dANmzGkGkGMKuhmXxw/1Aj++5Xjs67ZO6NYToaz2uHWBjGKz19RcfKsslOlU07DtZNk20seVyMmdTgC71qfH0K71OWvHA5D4GelPi1nExoCZJ7pfxHQbbWzGgdmnlv9ZiIio5vmW1FRKfRfApwD0a63PLPoFjLBzh8oo8SOZZvqB0Z48uuFl94OpNYLo03vkxEmFJAHVNJujiMiZEZJOmxVfQDJ2XZKNyYVY9JofQh35rVzFHumHXrkdqsUhce4yguKEVgP3r12EOS086aDiJcKNCJ1/c9Zot0SoESHTlGS61S5nJt/X7U5d5Em4jPCZeRIw62SOpiDvFdvmEtWIsDnhuPp5ONesJNOUkfFWH9lqj9s6gXWPwQjb2thQWBYFuvpx6QOHIu51ke2jMJ0u6K/YKn1g02T/t94lYo4XQfMu1mOPKytmV2yV5430Oc/QcBptzBqaRER1xc+zxwcA3A2gu6Rnh6JAVzfQs9Y2xbG7tBpZ1grmw38s7cBoGMAMjiCiAhkRmYZjXcW2puU4LXJlxeaOVVBppRBOhHJLnLuUROhom4kFM2bAMLjeLxVPaRP4z3vST1L+8x4YF33zeIzifWuyR/1YtaysWDVCLhekQkxoUmWEG537C/mmQnrFSvqzdAIVy3RJMJqme1yNHwHGDmeXXFixFcppJHwoDMxamLpfyChM+wX9qRGpg7j77+TiwcrtrNld78KNwMe/lt3PzdfmZpaaMeNS0ub13akyCJmx5TTamDU0iYjqim9nkFrr55RS7yj5BRIx4Nmvp59gP/t14MI7in8ta7quQ+0hHhjJc0ZIYnbJN2RBqdhYcnquw6ghh6nkeOhK6fA51dK0TnDWPprVEYzMmAcwoUklCisNfPi/y1RxWy3MEBKpGJ33p1KTOK1dvgO4+M7U1PFIs3N9wwjrvFKFxKe86y8Uy3ZhKq0+IZM+VIhIk9S4PGtVKnZf3g40tLrHVWwc2HlV+ki52JiUUwoXMHrNaRSm08JshgEoAJsvTU+AWlPVWS6kfpU6/RxIlZoZ6QM2XeRcBqG5Iz2hP+/P0kcbs4YmEVFdqekWXym1HsB6AOjsTF8JT5nJ2m2vp0/BUYtvLX7qizVd1157aMYCOagaEWD8MEdWUFFyxm58KlU83dLWCbXu8eyRF4UW43c6cV6xVRKniUkgnKP2FlFSzrjVZiqhCRyvhanWPZ7a1tTu2C7jwttTsW2a0rZaSX0jBMw4UU7E3aaXEeWRO3bjzv2FT95W+R1zujDFpA8l5YpbAFDNc6DP/QdZ9Mda6KdrM5QZd46rdbtTNeeHetNLLnzhvwrbqWIWZuOCQXUrZ5vrUudS5Zt+bucWW24XijrOkPO1+BTP2yinfO0uEQVPTbf2WuuNWutFWutFHR2ZV4iTUxjtrCmMxw4W16GypusCUnto711AbAJ4YAnwzTOATRfIAdQ0c78OUVLO2NVx546aTkicbboAePZ/A+NHAWjnOM8sxu82orPvF8C33gv8C2OY8ssZt6ZbMf5YKkbHB53jNRRNxfY3zwD23AzM+RNg9juBSAvw4KeAu850bmvjMWDoAHDkd3IbL+KkiOpGzthVLv2Faqx+zqQP5ZAzbgFg/HAqoQlIYqhnDRCfcI6roV7g8G9c+g2Nhbel1mi5tpOTF/hdThfs/ee092Lt7umu5HM0B6apMTA8iT8MjmFgeBKmqd1jSyecE/pHD0gfIrMvwT4EZcjb7hJR4NR0UjMXbURkyqJ1wLOmMH7/aklG9r9a+IHLmmpjvda5X8ouzL5jlSSOiMqkw02OHTVthCTOTv1rYNE1wNbLJZ4z49w+Dcw0ZXTb1JjzCY41pbeQGLZea+iA3DIBSnZuiSEjDG21n3vvco5Xw0g/CXl9t6yuqxOSfHdra+NTQP8vgQcuAr59ltz2/5InJVQUHYoCy7vT43J5t2yvNCZ9qAzaJSmu3drj8UFZTDCrHd4GjA9lt6XjQ/mP+aYJjL4tjxv8PTBse2xm/9ltqjrVl1DU+RzNoc01TY3X+4axbMNenHP7M1i2YS9e7xuG2TTXOba0du7vjvRl9yUmhtiHICKqAzU9/TwX0wgjFG2RKYxtpwBDbwJP3ywjLQEpGL3uMbnKnE/mVBud4MgKqpjh0Cy0dm2B0bP6+NQZs2sLNEIIDfUCH/58anr6UK/E9ZJvyMi2aHNqSk0iLlemR/qAxjbnwv7jg6n7uWKYdd8on0iTSy3MJgxFOnDwwh+gLWpi1IwCn9qFmRETHW0zEWmZAxztdW5TXaaoyQIBJjByKFX83/pdMW07ESAlOJ7LqKn53NeBC/935d+70PqERA7iKoKIw7E9EWpEODOuLrlbSigd3Cf9hnW7AShJoJsm8N1PZLelV/0r8K33uB/zTRM48gYw/FZ6229/bKFT1al+aA00zEivHd8wQ7ZnODw6hWu79+Hg4DgA4ODgOK7t3odd152DDiu2TFPOzbQGlHLu745mXLQf6pVFrNiHICKa9nxLaiqltgP4KIC5SqmDAP5Ja/0vhT7fUEZqFJoygK3L0x8w1Cur5rlJxOWE2V5U2qpvVcjKj0Qlaowfg9E4Q04mdAJQIRg6AdPqqBmh9Ng7uE/i+4aXUzFqJSGtUW6nL5GRSDvXpiecnr459Tq5Yph13yifhlmy0IT9JKWlA2iYhbHhGC7+3q+znrL3S+fhpNE+WRnXqU0NRbK3n75EbofelL+F1nnpv8/XthNlMhPAaF/6ttE+2V5pTPpQGQYxE6GLH8ScH111/Nh++OIHkTBbMG/eu2VxlNiYjKD8RQ9wzo2phYFUSI7foXBy6q1L2Rvr307H/NEBYPANYPcX3fsH1lR1Ijtt5r6fNBVPHE9oWg4OjmMqngCMBqBpTnZ/N3O18xVbgZ9kXKRq60zVl7Xzqg/hdB7JxYmIiHzhW69aa71Ka32C1jqitV5YTEITABAbBX77E2Du6YARBq7cCSxclPp9clqko0Qc6NsPfO9CmY7wvQvlfiJ5kHObTqNCxU/N5ZReyhAxAEwclTqC336f3E4chTJCqak1LtN8jxs/Ip2pS+8BVmyRE/Tnvg5csVOSn5/eA8w4ARjpTz0/c3SQPTbjU5I8suPoZLIb7QOevgWIT8r9+KTcH+1DNBzCwvb0xagWtjehrdGQE5nZp0kS/8M3yC/bOiVuWxekt7WnLwHO/QfbVLElwPk3F962EzkJNwIXfh0INyTvNyTvN1bn/QutT0i1zYf+nDJCeOytmUhctRv6hpeRuGo3HntrpvQXDEMWWYMhMznO+Tu50DQ+COx7QBKSE8nZGkbYpa6sLRbtx3zTlGnmsVFpv9k/oGKYcaD3Z8DcdwEzT5Tb3p85JhPd+g/RcEji8OiB9DI1r+8Gnr1DEvo37pfk+rx3A+d92aH0jUvcl9uHyHceSUREVRXcM8NQFDjlbEkIWVfqlm0EnvqqJHK6NssJc+Zq0s0d7lMar34cmLUwe2RFKApMDgP3n1fc1FxO6SUn8UmgZ21G/K2V6TDNc+RKb+ZV6K7NQLQldRJ17I+pkRP2aWcTQ8DsU+XEuaXDfXSQU2xaIzutEg4cnUx2iZjzaLdEDHNmRHH/2kXHp5AtbG9Cz7V/gebBX2XH8dmfkylhze0S6x1nSNtrxuUE+4El6X8bj1wno0O3Lk+9RuuC6n9+Ci5lAFOj6W3m0g3pCR2iXHzqz81pCmH1aSNQD0o7GmrrxOquzdBNyQVXDENKMA28lkr8WH2CZ++QEgtDB6T/4NSveKUn9WbWMZ/9AypXpDF5jnZxerxFsi8kzWlJ9R86WiO45YIFOH1uFBEMARMRuTB66T2SrN97l8Tg67uBC29Pn0LuNCLeTDjHfbl9iHznkUREVFWBTWqqRDz7gLJrvSSGYuMyAkMp505otMW9vpvFPp1mpA/Ysqz4qbmc0ksOlOm8+rky47JqY1sncNVuiWUzJld+/+NbwO+ek/htas9eXOXR6yXx0zo/NRoz15Qwp9jMTB6x7hvZhRtl1GRmTc1wIwxD4fT5M7DrunMwFU8gGg5hrjmQtWovetbIaOJty2XhisZ2YOBXwDO3AeffJKMnnNrmOX8CXP+CnKi0LgDCkap/fAoulZjMXvzvkeug1u32d8coOHzqzxmj2ckT1bMGyp48GRtw7hMsvk2SOt8+K6NfEZe2VoWBlzbLc+wzko79gf0DKk9swr2WZQar//Cj6z+Cmcd+g9BDl8njP3wD8J6/AR5K1Z8/fgF/pD87qe7U5zUMYN6fpce9F30It3rgCS5ARETkh8AmNWG6HFDMOPDPH5SD39WPp3fMWucBw3+UkUFu9d2cuKw+mXfqTanPo+nNCDnHn5EceTHUCzy4ROK3e2n643asAq582DmuZr8TmHVyYaNG3GJz7rtkOg/rvlEmbTomhnD1EwDkxKRjRnJ6byIOHHVpo62asTuukBh/5jbgQ5+RUcZuC14Z4fRFsoiK4VpXrQo1NWl68Ks/ly95Eo/J7A+nx7R0pOoYWv2Ka/YArcnRbabpPCPp0ntcLi79N+D6nwORFilvw7aY3LhcvHerZWkYCu36KPDQFfK4hYuAD6wFtlzmcgF/gXtS3WmGnteLAjnVA891HklERBUV3B6JlRiysxJDK7ZIp0ybqTpACxcBH7tJpp89ezvQ1Z1eeyXXdIRw1Pm98k29KfV5NL2pkFxttsffJXdn17bKPJlZuEhGXoQbnOMq2lp4kXK32Iw0se4bOUu4nNQnMk7qramLiZhzjFmJpNZ50kZf8E+yOnViCnhpqyx4ldk2R1vkBGVsgHWJqXiVqqtG9cOv/pyVPMl8Xyt5Mn5Y+g5Oj2mdD+x/WPrE63YnR27a2k/DkIRPOArEx2VBoNZ5Ms3X6fUO/z9ph5nQpHxynaMBzvVp7RcOzvsqMHbYfeaGW9kHq9blpgtk5tOmC6Q/kqvfUEqt3NYF0jcp9DySiIgqKri9EiMiUx/tBxSrRtaTX5a6bPZFJs65Ua7wDfUCL20Bfr5JRrzd8LKMFpp/pntCyG3hoHxTb0p9Hk1zGnj+PjnBsE40nr9PFgiy2FeGBlJJ+Se/DDz8t9mxv3K7jMooFGOTipXvJMUyMSRT1SONcjJtj7Hl3cBPvyPxfP7N0kb/81/IxSYVAv7sUmD/D2SK+vUvyN9Hy3xg47mFn6AQZQpFpea2PRaXbZTtRIXw65iZK3liJWOG/5jdJ1j+oCTt37MC6PhToHmuLNQyarswZF2A2nQB8K33Sjv8sZuAXz+RfeF1xVbgxPezJjwVJtrqHLfR1vS4sx/XI03yuIWLpLTC6IDLxffm7PO1eEySkkcPSP/j1L+W7VaZiLEB5/1025d8fYxQWM4br368sPNIIiKqKKXtiZQatmjRIr1v377UhtHDwOQxGQ2klCSEQhHg598Ffvrt1OPaOmWqQqRZTqAz3bi/sGkJTtMZCunYlfo8qiWqnCdnxe7IgFyBPtorcRkbA2Z1As2zgf/zJ6mTpY4z0usNTgxJJ2/vXfI6534JaH+HvMaME4uPK8bmdOdt3A4fAt7+TXZNzbl/AsxIjk6ITwJHfg8cfVPi0ghJbJpxaZ+fv1/a5yt3phZtsbR1Ahd/WxYRaukAZp4kJznWAm32x7Eu8XTnfZs7NZLdX4i2Aq28kEMFKuyYWXLsZsWtJR6ThUkyawKO9EkSpnUe8Mk7ZNSm1adoe4eMhN+2PNVeL++Wi0Z/eYP8LjYOvP1rmb1kXwBo8W3Szzj3S1KSJtLE/sH0522bO/q2/J3ouMzOMEJSwzUcBXRC4jbzuP7pPdLHHf6jbNv3gJSmsQakWMn1+WemL3o5flgWz7TX3lzeDezbJINYAPdzPetviH2MIPM2dm3+857PlvPSAICzT5tT3BMW31r2e1JglBW7lC64l5QSMTnJ3rU+ffXzd308PalpTVVwq2NY6NShXIuuVOJ5NH2ZcZneZV+Jd9lGoHGWdLx0Agg3yajjjjOAj/5j+omJVSh963Lg8y+WltAEGJtUnOa5QMtQ6iJRbCy1UMXQgeTJigZG+7NXmW4/BYACPnI98KH17vW2QhEZjbxyuyQ1j/2BdYmpfGbcub/Q/g6/94yCxI9jpmkCb7/uvOq6NV13qBd44h9kRlKkGZh7hrSl3/1Eej3CnWuBtY9mJ4CsPsXBfbKtqV0WYplxolxwZTKTitXYBvT/Mj3OVmyRRXuG33IpZTMpsRdtAQZ/D/zVF4F//4Yk2Vs65G9v5knpCc3+VyUJar9IasX6FTslqZnrXI9rHxARTQvBTWqaU8CvHpODljX9MTYGNMyQA6d9NJsZlwPk8geBnVeldwyb5siVOo5Wo2oxY8Af/wu46kcyWkKFZMREfAI4/BsZNTHSn5xSPtd9VdMnvyzTbBivVA2hMDD7NDnhMONSAiQ+DvzLx1MrlX7oWqm3dsVOmWb+0hYZ2blut4z2aZqdOgmxX4m43PwAACAASURBVGRauEja6pknySqlrQskrq06dqVejKo0jnYOBjMGHP2jxKE12q3358Csk/zeM6LcxgZktsbi2yThMz4o9z91p8RyW6eM1DznRvl9bEzaoqlRqS0/Pij9YSthGWqQPq/9d1af4qHV8nptp8hINbZnVKrxw8Ar30+do5kJqZn9kQWpuLUf109PzqQ7ekBGa768HfjwfwfO/qxc4J88Bsx5Z/qxf2xAkv1uC1tZg1lWbHUvE2H1MTL/hiJN3v5/EBFRRQU3qRmKAmdelj6Cratbrur97jng0nvloGRPYl56L3DZRjnpjjQBjckTbCtpZL8Czo4cVUqkCTjlbODBi9Nj96ffkdi1Rk3sWCWjKtxWNe3azJGWVD2JuLSXPWvSR2G2zpP6VWdeJiU+7NO/AElsmglJaFonIa3z/v/2zjxMrqrM/5+3qnpf0p2VSNKgyIDojCxhE5VRkEVGAiINSBZQNgGV+TmKiKPoOCguA6IsBkTIQiAIAZRdZRARMEGiIIsyAiFI9nSS3ruqzu+Pc2/VreVWV3dX1b3V/X6ep56qutt5773f+57lnvMeq/N7L7S/j7gsc1h75xI7xMyNY5fdSykMsV/dXiL5elBp/hEuapth6h6Z+nTjuylKmEkmc4fgHv9j2zD00KXwiZttI4zrP/c6Dg7/IqxYkNsTs2mG9cHenvTuuob2tA/z9oZTlFEhuXU0t0zw0KXp/D+l2S9l+ufjfwxPXgP7npYevdGQNYzX7WXpTmyVMxN5nX2RVWg0U+M0mLfS9h71lkFOWWp7m2qMTEVRlKqgekstiSE7vMDbg23FAjj0s/b33edB7+bM9XefZ+O8SNRmZDvW5faCKxRQWlFKwVB/umEIcrV774X2jbH3TbOXtg5o3ZXk9PewqTfBm9t62bRzgGSyOuLjKlVK9/pc3d5zvtXqoZ/N9cd3OJpu68BEa3lzez+JoQG7bt1qW5E++nI46aZ0ZcLdd8V8m14kYhsJz/qVDc1w1q/C02joNtBq/hF+Bnvy+Nz5drmihBmTSDf+QLqMYBLw8n22B5vXf+57WrpB07v94RfbWG3ucODsdW7vzLD4V6W6iQ/kLxMkBqxu3fz/jPtszPhs/3zvhVbLM97jr0u3l+UTV+VObNW52D4jzTMLN0xGIrajQXYZ5PZ5tgyiKIqiVAVVW3IxfjHZ3KHoXWttbKHs9U3TbEbYu8kOwdFYKkqFKUq7bq+JaG3urKZzr8XUNtG/YyPxra+z/h9r+erKP/Hyhp3asKmUDZMYyq/bhnar3byajmE6l/Ld323jsCse5YWNA2ktr1ttKw5+z0NiyP5249i1zbbfYalwayyuqsHP55pkPBiDFKVIjEnm9zMm6ZQRajLXN7Tn337KnnaSrHzrJu9he2eO1L+6s693vWG/h5sxWpkw+PvchNWtm///6ut2eLnfiKRojb8u3ZEc3RttI+lxP7Bx5s94ACbNtp9YzfDGJnzycrcMoiiKooSe6u1XH4nlH26QTKTjszVNT8fXXLfaiZsyw+ml+aaN21KueG2JuH3LlxhyMuVddBiDYimkXbBDcZqmw/y77bLJ78ycnGX6PjDYTSNxGltrmfmPB7n8sIP4yiMv8a0T38u0lrpgzksZ15hIDZJPt0O9VtOn32E16sZp696IidXy4Lparnv8OQCW/Xkn/73wPqImbnvMR2K2QpF36FhNuGNWhj3ep5LGz+dGNE9Wwk1caqnJp92ezbZ32lBvprb9huJKpMCEmfXQ32V7LifjxZVZNfyGUghfnxu1L+rvOd+GrTns320D/el32Hjy61ant22eYXXom4ZnJMdYyghRn7w8WkSDqKIoihIKqrbkkaibZBssM4YbLIUX77Xx2e77AlxzoI3F8uGv2YaiU5bZN3fuBBRrlucOWSgUULpo4+Kw4Xn42bFw9b72e8Pzdrky4TF1LVarGdpdYmNqurGFlp0EP9offnYM9GyA2QdjJu+BmbY3ZmAH0rUW7jrbxuXc7RCmbPwD5xzQymA8EezJKeOWruhkkp1LMnV7wvXWpwLUtdoK9Zrl1gd/8g7k6Rs4qGUz+81uZb/ZrfznQRGitxwHV+8HD15ih6IhNnbspx6yPn2v4+x303Rbab7xSLjqPfZ74wvh6Q3k9hLxXo+wxPtUMqlvy/W5pyyF+vZg7VKUYZBYnS0fZJcXapts77Qp74SFv4QLVsFnn0mvzy7Xtu5qG4jyHStSA12vw80fTZVZzYbnScYLlFk1/IZSgIH6KZisOpo5ZSmydhX8+jI7cetB58DSE21d7b4v2HLDrDnOtsvYXjeDTb2JwiOQxjqSIxGHgZ25I6JOWVq4QVVRFEUJFYF1UxCRY4AfAlHgRmPMd0ayfzTRb4NAe3uwxerggDPgxiNyY7PMu8tOCuC+eW6cBh/6SnpWyaZpNkN0Gz2BZNKwpWeQwXiC2liUKU21RCIyvHH5Ys+tmA9nPgCTZo3kNJVxiAz1Wa16tVvTCP/6ZTAmHSwdUtoxZz6AbH01M5D5CdfDr5xYRAt/wcwdg9TEosGenDJukUiEvlgrTaffaf3ottet34z3w62dmQH+n7oODvscPHk1U168m69+5A4AmlY6kwbMmmMnv3joq7mTYJyyFFpn2t70O/9hJxLqWpuuNJ/1K+urg+7FWapeIkr5Geqx92feShtru2cT/O8V1ufOeI/eMyW0RId2wmPfzZz9/LHvwjHfto1AAzvTcTLdydsmzYL5K+22fdtsT0ywM1I3z4Az7rfxBiMxTE0j0rM5Jw6nrJhP8oz7SbbOyl/u1fAbSgHqEv1IVh1NonXwjg/Aq7+BuhZY+vHcGN3zV2KitXz3iR1c9/ijzGpv4IYFc9hrRktx9a+R0r3eTmbUPD39jA312udER9cpiqJUDYF4bBGJAtcAHwHWAatE5F5jzAtFHyQ+kJ5Vz6WtwwadzlfQwmRWXNwK6ceuzFshTSYNL2/YydmLV7NuW9/IMla/2HMan0UBO9Qmn3ZPuM4WpPJoR+IDuYHM7z7PFsJunwcmSVtLM/VNOvRVKQ9tye3IrXOt9hb+AmoboWcj3P2Z3JdIR19uhzE6y2Y2R0gkTXq7wy5Kb5c9Ccbt8+D0O23vDe/svOtWpyvNYRn66PYSUcJNYhC2v5Ge9dlBNjyXbiRXlDCSdCYEevm+zOXHXwXtu9veldkNQ8f9wP6P1tkhvU0zbAO+OzGm4y+T095FvGsdtT6xNk18iK09g/lD2mj4DaUQQz35y7nzV8KcT9vG+Hz1pJ7NDDS+jesefx2Addv6OHvxalaef1h5Qiu59TW37OHyuTWlT0tRFEUpG0F1TzgIeMUY83djzCBwGzB3REfwm1zCDULtpa0DovW5wwILDFvY0jOYatCEdMa6paeIt9DRGh8bND6Lgn9Q8qZpsO3V/Nrx07szoZCJxKifNKM8b7IVBRCvbpMJuPMsq1k/Lfdts//bOmhoaGTKpJa0tt3JLPwmtRBJ/773QtsI6hwrNdGbDn1UiiWZsL2FtGeZUmWIG5vQS1sHDA1A0ucFek2j/bi+c9/T0g2a7ja3nUaiexMvbx60I0TypNGfjPiHtNHwG0oBxK/MKhG4YyE0TsmrOdP6Nm5a05OxeN22vvKFVtL6mqIoyrggqEbNXYE3PP/XOcuKxw147sUNQn3C9bmxUWobbIW3yFkaB+OJVINmyshiM1a/uEUan0UBpJB2H7siN1bsKUvTk1pl7zPUC51LkOYZRKI69FwpI27PHIC6Zhvkv6Yhvy6bZ8C0d8EFqzALf0l/whAhCZ2L7Xp3Mgv3O3v/pMfPehrvU5VmHfqojIRILD2hihftWaaEndqmtN+cNcdOqHLG/bZBU3zKEu7kbUdfDtP2tj3Ym6dnbte1lliin2V/3kl3IpZOwzlGsnMJ16zqpjY7pI074/mON+3Lq7MfhYuetz2edZIgxcW3nBuzo5IiNbn1pJNvQZ6+gc/sX88fP7sXd87fg/1mt3L0PtOYHtlRdP1tRGh9TVEUZVwQ6oAhInIOcA5AR0dW5hhrsIUwNw5QW4f9Hx+0Fe2MWJv19k30W3+yjUbdG+HUW22BbKgv70yPtbEos9obMho2Z7U35Bbw8hGN2ThdZz6gs59PUEal3aEBq836dvjY1VbHzdPtN5KeMdIbe7CuFVbdBP9yMrS+DRom569UBB1/UKkKCurW7Zlz22nQMhMOPAse+LIdHu6NiXnyLbZn/OKjbOiEtg5mzr0W6neDx75nK9qTZtntfvv93P07l1hdn/+0nTzr1d86oUXud54FdOijkkNhn1sPkzpyfKg5ZRmiPcuUACmoW7CTXLXE4YwH7MRqW//Pjuho3gWGtsOJi2DlOZkxNWubbPn3iavtsHV3+a8vy5hdWrb8lS/Pmcq3Hu/i8x+YyS5n3AfJBH3JCD96eifH79/BFG9Im7CE/VBCwbA+N6ecuwSevgGevDpdVkiVdWdYbe15JLL4eCZ3rWVyWwd3dC5FYo1Ef/YRT9l3mS1DJIbsyKexlGm1vjYhGdbvKopSdYgxBWaVK1eiIocClxljjnb+XwJgjPm23z5z5swxq1evTi/Yud728pGoHapojA18XtsEm16yBbq+bfDEVbah6JN32Pgubny2phlw5GW20bOh3ckMJZWZjSmmpjLeGNMNz9Hu9nVw/5fskDA38P+a5XDUN2H7m/D0T+CQ86B/u214b5lpC32JuO2dYZy31I9/H55dan+3ddiG/Ja35VYwtCIyUSmtbiGzcdyN5TZrjh3i2DTNNqqbJPz6m5kx4Nx4xz8/0/4/7CJo2QVqW6B+kq2sm6TtxeGt9HQutpX6hy5NV85PXW57H216STU9fimpds32dchTP4EDFlp9SBT6tmJaZiIt2iNHKSmj1m5en5uIw4bn7eRA+54GbbtBQxsM9thyQXzA9oozSTu0d8c/4NffsOVeN+Y2pMsIy07OjFXcvZHnjr2Lj/3srxy1z3S+etw+RCOSf3LM7g1w45G5L5M0Lu14oLTlhb4uW7ZNDNk6WrQW/nCjzdvBlhsOv9jqefNfbRn4mG/DLf+Wqy9Xt95l81bamdM1/1fKUdZ1eOq688ZyaAAOeceUke1w9H+POU2latAGpRIS1KuoVcCeIvJ24E3gVOCTIzrCUF86XpDbMPTXB+Ggc9KTAXgLbpGo7fWWGLDD0wEe+Xq6onz8j21j0uFfghnvIRKNsdeMFlaef9jIZz9XlEIkhvIH/j/6W1arYGeGvOeCzN4Xv77MVlQ+foPtgXHwubZhx51ApaYxc3ZoF7/4g1oRUUaKE4fYbH0VcfW0bnW64vy5Z21jfLa2u9bayvax37O+++7zMnsc/+8VcMTXwJ2IyN1nxQI7sYB7PK92deZxZSTseWRmJfj4H9uGeEUJM93rbYPmwefaMurB52ZO+HPKMmicDFe+O3ffhvb07661MGVP+3Kpb1t68jVgn+l1PHHxh4Yv52rYD6VITH8X8trv4B2H23AyJpnZoPnhr2WO0Dj+x0D+Cauoacxd1rtZy7SKoihKikB6agKIyEeBq4AocJMxpuCridzebm9CImGjgro9NZMJ2PI3O8TcM8SG434AM/7Z9nJLxm0sl1gdxPvTme3qm+HQ8yExiHF7DEVr7f9IDWIStidoMgmRKIlIHdulhbqooWlwi3PcKImaFjbHa4lIlFhUiJKkZWgLkhzCROywhkiscFtyMpEg0b0JSQxgonVI01S29SVG1riaZ7hxEmFLz+CoG2mTSTOm/UtNKewp8hilfQvY9Qas/QN0HJjW7mCvnU06mYDeLbZHW/bbarfXRVsHnPmgNcvE7T6RWOpYxtVtrB6J90FNAzLY4/TmcJ6TSNTqMd4PsToMEbttJIbE6pywDQ0kG6eypTee9/r4XTt3uUkmaGcHMTOIiNM7KhIh2TD8MZPJJAkDxhhqY1HaG2rYMTBE32CChDHU10SZ2lSXkV4pdBmUxoe7lsUuz6Lkb6/j/f1E+zdBMo4khuD3P8zsLXzGfba3kNtrSKJpvxuttf9vOipH2+bMB8AkkWTCCdAvtuIdidn4ndFaZ9bzobR2wVZ2BnbY48fqHR8dd3rwWzuSEiNuYCutREVoZ0de3yoi1EYNLYntxJJDJKO1eX0vwI7+QXoGEsSThppohOnNVov5tFvongFZz8oQ4mmgjceTbOweYCiRTKUTi0VIJg3b+wZoHNpGzAwRidUhTU6jbshDTQShXdP1BvLAxTm9482xVyBts8eSlKJkU9qemltfhcbp0L/F/r/5uNyywacehg3P5Y5QOvpy+9vpSW9ad7UTD0nEDtsVAZPEGOP4a9dnO6NCIjFbVk4MppbLjjdtjO8nrrLl7LYOzBn3k2ieAb1bicb7re+K1NNX00r/YJLW5HZiZpBkpJbuWDt9Q8n0s28StoEqMZQqR6casRJD1qcbY3ulJhM5w429/qS5LkLD4DYiSZtWpHkakUg0v7/x+EkTraUrMonBuMnru4NmrOWSYHzuWqR+itWtU+Zkx3p4+BI4/pr8M6OfcV9+fc9fCb+7Ev7pmHRD/dR/StfhYjYsjUkO2v/RGuJSy85IKwNxAySZzA5iySEiDa3IwE5Ha46+jcFEa2CwG5JJhiJ1bJVWIpF0OTODRNz2Wk4MOT3/I/ZYTdML57XJJKZnE8n4AHGpobemnUkNeY4fBCEtNwRV1nUJpKdmEGjv0KAIwcM/fggsaIgx5n7g/tHuH6+bQnTrS4j7Bjv7jZ/7FrprLUx+py3grZiXGcPwse+le2p2LrEZ5OLjbQ+ktg44eTE8fxey90dtpfrnZ6T2j524iEmT9yDa9Q9kxfz08s4ltNVP5fO//AeXHLsXuw29mlovbR2YziUkp7/Ht2EzmUiQ3PACNSs+mTpmvPNWfvpshOsff624YfB5hhubU5fzenQ35t+0alTD6cM2HL8U9gR1TqZ+MjJ1DxuPMFu7c6+F9t3zv612h0k2T4eBnbZi4Y2x6fQ2lg9+0er2nz8Om/8OU/dI9/TwpCWe3p9y4iJ45Kv2OelcDKtuhFd/i+m8la/+qo+HXtiUcX2AvNduz2nN/G1TN1c98hKXHxaj5hcLc+xLHn5JwWNe+cjLLHzf27n4zj+njn3zmQeyrWeQf1/xp7zpleIeBqUHv3T9zq2U5zwS4v391ud6/B2di+3KV3+bjpe155G2R9EHvmAbx7PjwDZPz9R311okPgAP/2du/De3Z3J9W7oS5Gp30ixbsVgx3x7ziMvyPg/Rg88l+vRPaHz/fxJJ9lOzckGGb3W1ePQ+0/jxEfXU3GF7QUWz1rvXua0xxqadg5y/7I8Z+hyKG678Va52/e7Z4k8dxEA8mf9ZOXU58al789KGHs5b+kxqn+vnHcBe05tZ19VLe/ffqLtnYYaPl5APyw8sH5Fo/nKCaNw0JdyYxunI1r9ZP/eJm3LLBs3ToWdj5giludfaXsjPLsvoESdtHXDSjVA3yYYIcZ6JVJn3hOtt4+EdCzN9fF2rbSx1X7Z6RzcdfC7ywMVED/+SLY87Prxm7rXIpA5i3duovyudZ7R2LuO7TyT53d+3suLsg5gZX4f0bcuNC1rfahuPfn5Gfv9+6nKS097Fyxt7OHvxat7/jsn81/siKf/t+ve36t/BKTc8nelvpjcR2fRiyk9KWwexExezNrIbF9y6JhRlXJex+szAfG79FHB1642p+fFF0L0pfxk3EYfOpZl1tbnX2lALh342XQbY6zg4/It2JEfzdDsCZLAH8eij5qQbaa1r5werBjlr70HqfrEQ9psPex6VadPJi2Ht08huB6fif9a2ddBwwmK+9NshLvrI3pnXKhGHjX+xHQyyn4UPXQLT3+0b195sfAG57TSiTvmib+4tvN68J7tNaQ62YTOkIarCVu9UFCXcBF/LGSXR/k22cr3vaemKCthvd1g6WOccjaUzSXebFQvsvqn/8+1bN+82dyyA/U63ha2+LZnrVp5DLNGfruB7jlMvCc45oJVpdOWslxXz7XAiHxLdm4i5DZrOPrEVn+TcAycBdgb2sxevZktPgeE+eYYby22n0b11fWrio6KO42FLz2AqYxnN/qWmFPYEdk79W63e8mn3nvPt8Nx8s0bW2oY/Dr8Ytq9NF/Ddfe+90B7T1e2KBbY3aKG0DrsopefU7xULbAGyay3RFZ/knANac66P37Xb2D3A2YtXc84BrUxxG2my7IsNc8yTDpidahRyt3lja1+qQTNfeqW4h0HpYbhrWc5zHgkpn5vtRw+/GBb+wjacdxyU1mHfllyN3j7Pbu+lrcNOfuH1x15t3nW21Xu2diWSrpwcdpH/8+B8T+p/gxa3QdPZxqvFcw5oTVeI86x3r3M8QapB013+xtY+zl6SX7t+9+z1Lb3+z8ptp5Hs3pRq0HT3OW/pM2zsHqB763ra7lmY4+PpXp8/1ETvprHc+pIRmM818fzlBDNU3nQVZay45YWutbYMkF02OPzidAMLpP1jfxfsPz9X93eeZf1pvjLB3eflDutdscD2QvOOHnGfnyO+ZjsQvHxfujzusSGWGKDxrvlZPvV0Lj58Kuu29TEpsQXZvjbdoOm1v3tDutydz7/fdhqJ7k0pf3Lx4VPz+u/mxLYcf5Pozi0jt6xcQKR3S2jKuC5j9ZmBl3Oz6kckEvaFfL4y7tZXIN4Lp99pe20efbl9uXn7vMwywL6npScgOuwiq9lsfdx5FrHtr3HBgc3p/PVfOnNtumMB7H1M+njO8kl3L+CcA1pzr1X3+tznzS1r3PZJ/7y2d5PNoz37td2zkO6t6wPXmG+IqoDLDWGrdyqKEm6qtlGTZNw63ob2/G/8GtrTb5mN8d/G+18kd5tI1H7ni+ni2pC93CSY3ijUSSLvekn6V6QkMZB3n4ZIIvV33bY+BuMJfPGJe9RWm8xYNOxxPAzGExkzwY90/1JTCnsCO6fhtDuw3fZocwt97pvguNPY2f52q0c/TXt1W8xzku93JJr6Pb0x/Vy418fv2g0lkqzb1mf3KWBfoWO2NdTkHLuxNpo3vbiTXvby0dzDoPTgl67fuZXynEeEn79LJuzkVy/fl9ZZQ7u/Rifvkavtx67I9cdePebzv8bjXwvpexh7XC36aTZbq0ljfPWZT7t+98zdxy9dSQ7lP1bSWF+e73y9L+a8y0MS8y44n5s/LyYZTP6lKEXj9bvxPusvvf6z/e0+2o7bHpz51tU0+vvM4Xytd3nv5nSoJ78ydYHybJ0k/POJmsa0LT62SmIw5U8aIvnzpzrJfMbXbevzLWePpYxcLsbqMwMv53pxNfHEVbk67lxsywHJhNXtzcfZxkNvzHgXrx4KlTVqGqmPePJK45Nv+iyf3ii518ovj3Vt8strC9TLgtZYWGPlhq3eqShKuKneRs1IzGaEfdvyv/GbNNvOeB7vt7ND5tumb1vm/+z4om0dNoNt67DDKLPXuTZkL5coG3sNAyaad30qHlweTLQu7z59yWjq76z2BmpjUXyJ1eY9Rtdg5u0e9jgeamNRZrU3jHr/UlMKewI7p+G027fNDvc67gdw4Wr42NV2aEtdi31z3b3B6tFvX69ui0kr32+3st/Wwcbe9HPhXh+/a1cTjTCrvcHuU8C+Qsfs6hvKOXbvYCJvejEnvezlo7mHQenBL12/cyvlOY8IP38Xiab15f3206gxVttuTwxnBt4cf+zVYz7/Kx7/Wkjfw9jjatFPs9lajYj46jOfdv3umbuPX7omUpP/WBGxvjzf+UZr8i+P1RIGAve5Xlz/qChhxqvd7etsWeDoy9P+s3uDv+/z88FDvf4+czhfm51Gof8mv29zy7MDJlrYRtcWH1tNtDblT/qS+Z/xAZPpW2a1N/iWs8dSRi4XY/WZofO5xtiGyt980+r3Uw/ZnpkDO205wHvfvft5l3n1MIzO+5OevFJ88k2f5Rt7Te618stjXZv88toC9bKgNeZnW9DlhrDVOxVFCTdV26iZqJ+G6VwCa5bnf+M32GNjBtU220yoc3HuNmuWe/4vycys3Fgrzy6DExdBw5TMdScuIh6ttzZkHHcJ/SbKomd2sIm2nPWmcwk07+J7XtHmacQ7b83YJ955Kz9ZtR0gFVPEnWQiL43TbDwUb7qnLqd58i6pDKKo43iY0lTLDQvmjHr/UlMKe4I6p4LanXstTOqAaJ1ddvd58IvPwSGfgZXnwkNfgcapdobHudfm9nhbszyt287FsHaV1bZfWk9cldJz6nfnYnjyR9DWQaLzVhY9syPn+vhdu+nNddywYA6LntnBlo/dkte++DDHvPOZN7jipH/JOPbsyQ1c2fle3/RKcQ+D0sNw17Kc5zwSUrrN8ncM9qR15+pszXLrM7M12rkUnrnF6vvuz9ieGG4cV68/9mrz4zfYZyJbuyZp02/rsNv6PQ/O9/b62ew8cXGOb3W1uOiZHQydvMx3vXudY1G49vT9c/R5w/z82vW7Z7tNafR/Vk5dTqR5GtfPOyBjn+vnHcD05jqaJ+9C19xbcnw8zbvk+H5OXW7zhBAQuM/NyosT9eG4LoriR4Z2n7jKlgUe+ortyfbQV+zLzmy/7Pq+SR3wiZ9lrjvpRrs8X5nghOtt+SK7rJyM5x4ny2enyjTu+rnXEo/W0fvxJVk+dRlXPLaZWe0NbI9OwUxyyh/Z/r15Rrrcnc+/n7qcaPO0lD+54rHNef13d7Q9x99Em3PLyDtPXEyycUpoyrguY/WZYfK5tp7lNCivW231mxiyDZpPXW910DIzN78/cVHmsjXL03W6J66yms3Wx0k3Ep+0O9es6k7nr39ekfusnLwYXnowp464/YTFLHpmR+61at4l/0iqNcvh1Fv989rGaTaP9uzXNfcWmifvErjG8tUZw1BuCFu9U1GUcBPY7OcjpeBMvO4M0sbYeaRi9TaYs3Fmha5tsXFa4gPp2c9r6mzsTrj9JgAAEu5JREFUQne23WidrSQnBtOz4kVrITGEicTSs5+bJMhws5/XEZFICWY/t7My6uzn5bMn8Fmks7UbqfEsSzizK9ZYPSb6rfZqm4nEBxCMnaHU0WRqv2idM/t5XXr286F+z0ynSTtBRiRaodnPhxCREs5+DvU1EZ39PODZz4nEoH4y9G2yPR0cf5k5+3nEmf08YdfXNMJQjz2YSdqP62vdmUyjNSBRTMLVjdgZSocGUrOfU3D280Q6bd/Zz3N9a5hnP48nksR09vOiKUa7ifppxOrrx5KMouSjtLOfk6XdWL270PrBaMwm6S27SsT6wmitU5ZwyraRWHq9Z/Zzip393BhIDFgfHKu328UHMJEaks3TU7Ofm0iEhGf280nJ7UTNEMlITYVmP7dp6eznI9q/MuWFQSe/du91pCZ9jyMxECERqSMa73U062wTq7MvUJNOvS7mKTPUNNr9fWY/F5Kp/DVSX8LZz5ND6edGZz8vk1k6+/m4RWdcB539vKRU9dirWH091M8ucuvmUaeTT3ExIOWmGhszluf2w5zle5x8RKJRIpMyjzKtZYS3KhKxb7q9i4BpLXUjO07GIWVM+5eaUtgT1DmNTLtZ+xa5nZ/e8i3329ZqJv9QD79rl7m8MXf9KI4JMDlWB00j22ekBKWH4q7l8MvLTV7d1ue5KQVpH34TRpDTN0wquDrqfGamlmRqMte3Nqb2y78e2hrraMuVdsF74nfPCj0rsViEt7U15CyPRIT2pnq8Z+VZmeP7w0RYtFvVhR9lQjGW8kIlEJxhX627ZPyvAVobwOvbJufsHYMW/9FLw5HjTxpzfWJef+Pxk0KxuVIwjNVnhsXnAkWVF6xvznNHGnPV40cN2VrzpNvQlrO9eI5fS756nIdoDCbtWrQtKSIRpGVGqkwSntoUoS03hK3eqShKeNFyvaIoiqIoiqIoiqIoilJeHrq08mlq79BxTfB9yxVFURRFURRFURRFURRFUUaA9tRUFEVRFEVRFEVRFEUpEU/9fUtJjqOxOUtApXuHas/QilI1EwWJyCbg9SI3nwpsLqM5lUTPJXg2G2OOGe3OE1i7I2UinzuU/vwrqdt8hPF+qk3FEbRN5dRu0OeWjdrjT5hsgeLsGbV2x+hzw3CtgrZB0x99+pUuLwR9rSrNRDtfqNw5B1HWrab7qbaWh1LYOibtKplUTaPmSBCR1caYOUHbUQr0XCYWE/kaTeRzh/F3/mE8H7WpOMJoU6kI27mpPf6EyRYInz1ewmBb0DZo+sFroFiqydZSMNHOF8b3OVfTuamt5aGabJ0oaExNRVEURVEURVEURVEURVGqCm3UVBRFURRFURRFURRFURSlqhivjZqLgjaghOi5TCwm8jWayOcO4+/8w3g+alNxhNGmUhG2c1N7/AmTLRA+e7yEwbagbdD0q4dqsrUUTLTzhfF9ztV0bmpreagmWycE4zKmpqIoiqIoiqIoiqIoiqIo45fx2lNTURRFURRFURRFURRFUZRxyrhq1BSRY0TkZRF5RUS+HLQ9Y0FEXhOR50RkjYisDtqekSIiN4nIRhF53rNssog8IiJ/c77bg7QxTIwn7Y6Gatf7SBkvz8dwuhWROhG53Vn/tIjsXgGbZovIoyLygoj8RUQ+n2ebfxWR7Y7e1ojI1ypgV0GNi+Vq51r9WUT2L7M9e3nOf42I7BCRi7K2qfh1KidB+9kwPfd+z0mA9tSLyB9E5E+OPd9wlr/d8R2vOL6kthL2OGlHReRZEfll0LYUIkhdF+NvK2RHxr0KIP02Efm5iLwkIi+KyKEVTv/fnev/vIgsF5H6SqZfLEH74CCYCOXbMOVt5aZaNBwW31wsQfvwYgna1yv+jJtGTRGJAtcAxwL7AKeJyD7BWjVmPmSM2dcYMydoQ0bBzcAxWcu+DPzaGLMn8Gvn/4RnnGp3NFSz3kfKzVT581Gkbj8NbDPGvBO4EriiAqbFgS8YY/YBDgEu8HmeHnf0tq8x5psVsAsKa/xYYE/ncw5wXTkNMca87J4/cADQC6zMs2kQ16nkhMTP3kx4nnu/5yQoewaADxtj3gvsCxwjIodgfcaVjg/ZhvUpleLzwIue/0HakpcQ6LpYf1tusu9Vpfkh8KAxZm/gvZW0RUR2BT4HzDHGvAeIAqdWKv1iCYFWg2S8l29vJjx5W9moMg2HxTcXS9A+vFgC8/VKYcZNoyZwEPCKMebvxphB4DZgbsA2TViMMb8FtmYtngvc4vy+BTihokaFF9XuBGOcPB/F6NZ7Tj8HjhARKadRxpi3jDF/dH7vxBY4di1nmiViLrDYWJ4C2kRkZoXSPgL4P2PM6xVKLwgC97Nheu4LPCdB2WOMMd3O3xrnY4APY31HRe0RkVnAccCNzn8JypZhCFTXYfC32feq0ojIJOCDwE8BjDGDxpiuCpsRAxpEJAY0Av+ocPrFELgPVspDmPK2MlM1Gg6Dby6WoH14sYTE1ys+jKdGzV2BNzz/1xHSh7dIDPCwiDwjIucEbUyJmGGMecv5vR6YEaQxIWK8aXc0jEe9j5Rqez6K0W1qG2NMHNgOTKmIdYDY4e77AU/nWX2oM9T1ARF5dwXMGU7jQfqBU4HlPusqfZ3KRVj9bODPfdZzEpg9zvCzNcBG4BHg/4Aux3dAZe/ZVcCXgKTzf0qAthQiNLoext+Wk+x7VWneDmwCfuYMn7xRRJoqlbgx5k3g+8Ba4C1guzHm4UqlPwJCo9UKM1HLt4HnbWWgKjUcoG8ulqB9eLEE6uuVwoynRs3xxvuNMftju7hfICIfDNqgUmKMMdiMXlFgnOt9pOjzMXZEpBm4E7jIGLMja/Ufgd2coa4/Au6ugEmh1LgTF/B44I48q4O4ThOWIJ77Qs9Jpe0xxiSccAizsD1i9q5U2l5E5N+AjcaYZ4JIvxoZxt+WM90w3KsYsD9wnTFmP6CHCg61dWIVzsVWuN8GNInIvEqlrwxLKPP+SqJl2uAIyjcXS0h8eLEE6uuVwoynRs03gdme/7OcZVWJ8+YVY8xGbJyzg4K1qCRscIdTOt8bA7YnLIwr7Y6Gcar3kVJtz0cxuk1t4wyLmwRsKbdhIlKDLcQtM8bclb3eGLPDHepqjLkfqBGRqeW0qQiNB+UHjgX+aIzZkL0iiOtURsLqZwN77n2ek8D9kDOc61HgUGwYhpizqlL37DDgeBF5DTu88MPYOFpB2DIcget6OH9bZnLulYgsrbAN64B1xhi3F9TPsRXfSnEk8KoxZpMxZgi4C3hfBdMvlsC1GgQTuHwbeF5SBqpKwwH75mIJgw8vlqB9vVKA8dSouQrYU+zslLXY4XT3BmzTqBCRJhFpcX8DRwHPF96rKrgXWOj8XgjcE6AtYWLcaHc0jGO9j5Rqez6K0a33nD4B/MZ5Y182nNh3PwVeNMb8j882u7ixPUXkIGxeWLbG1iI1fi+wQCyHYIcQvkX5OQ2foeeVvk5lJqx+NpDnvsBzEpQ900SkzfndAHwEGwPsUazvqJg9xphLjDGzjDG7Y3XyG2PM6UHYUgSB6roYf1tOfO5VRXspGmPWA2+IyF7OoiOAFypowlrgEBFpdO7HEYRz8oqw+uCyMcHLt9VWpi2GqtFw0L65WMLgw4slBL5eKUBs+E2qA2NMXEQuBB7Czvx3kzHmLwGbNVpmACudumQMuNUY82CwJo0MEVkO/CswVUTWAV8HvgOsEJFPA68DncFZGB7GmXZHQ9XrfaSMh+fDT7ci8k1gtTHmXmyBaomIvIINIl+JGVkPA+YDzznx+QC+AnQ4dl+PbZj4jIjEgT7g1DI3tubVuIic57HpfuCjwCvYmcjPLKM9QKqS9RHgXM8yr02Vvk5lIwx+NmTPvd9zEpQ9M4FbxM4uGwFWGGN+KSIvALeJyLeAZ3EC9AfExSGyBQiFrvPqyOnZPZH4LLDMaej4OxXw3y7GmKdF5OfYcCFxrDYXVSr9YgmBVoNgQpRvQ5a3lY0q07D65vIQmK9XCiNVWj9RFEVRFEVRFEVRFEVRFGWCMp6GnyuKoiiKoiiKoiiKoiiKMgHQRk1FURRFURRFURRFURRFUaoKbdRUFEVRFEVRFEVRFEVRFKWq0EZNRVEURVEURVEURVEURVGqCm3UVBRFURRFURRFURRFURSlqtBGTUVRFEVRFEVRFEVRFEVRqgpt1CwRIpIQkTWez+5lSkdE5Ksi8jcR+auIPCoi7/asP1lEXhSRR332f1ZE9nV+x0SkW0TmedY/IyL7j9K2y0TkPwqsP1lE/iIiSRGZM5o0lNKj2i1Ku98TkZdE5M8islJE2kaTjlJaVLtFafe/HN2uEZGHReRto0lHKR2q2+F169nuCyJiRGTqaNJRSotqtyife5mIvOm5Rh8dTTpKaVHtFud3ReSzTnn3LyLy3dGko5QO1W1RPvd2z/V5TUTWjCYdpbqJBW3AOKLPGLNvvhUiIoAYY5IlSOcC4H3Ae40xvSJyFHCviLzbGNMPfBo42xjzO5/9n3D2XwO8F/ir83+piDQBewB/Gs6IUZ7T88DHgZ+MYB+l/Kh2h+cR4BJjTFxErgAuAS4ewf5KeVDtDs/3jDH/6ez/OeBrwHkj2F8pParbIhCR2cBRwNqR7KeUFdVucVxpjPn+CPdRyotqd/h9PgTMdWwfEJHpxe6rlA3V7TAYY07x7P8DYHux+yrjB+2pWSZEZHcReVlEFmMb82aLyBdFZJXYXjPf8Gx7qfNW5HcisnyYt2gXAxcaY3oBjDEPA78HTheRrwHvB34qIt/z2f/3WCeD83094DrLg4BnjDEJEfl/IvK887mowDmlbAf2KnRNjDEvGmNeLrSNEjyq3VyMMQ8bY+LO36eAWYW2V4JBtZuLMWaH528TYAptr1Qe1a0vVwJfQjUbWlS7SrWi2s3LZ4DvGGMGHNs3DrO9UmFUtwWvjQCdwPJitlfGGcYY/ZTgAySwbyfWACuB3YEkcIiz/ihgESDYxuRfAh8EDgCeAxqBVuAV4D980mgFtuZZ/nngf5zf/wvMKWDnbsDfnd/Lgb2BR4EW4FLgvzw2NQHNwF+A/fKcU9G2Z9lQ0Eb9qHbDql1n318A84K+b/pR7RarXeC/gTewhcVpQd+3if5R3Q6vW2xvoR86v18DpgZ93/Sj2i1Su5c5mv0zcBPQHvR9049qt0jtrgG+ATwNPAYcGPR9m+gf1e2I2hc+CKwO+p7pJ5iPDj8vHRndw8XGvHjdGPOUs+go5/Os878Z2BP7sK80zpsREbm3nEYaY14XkVoR2QXrcF4GVgEHY9+s/Aj7NmalMabHseku4APAvVnn9IFK2q6UDdVukbaLyKVAHFhWshNTxoJqtwjbjTGXApeKyCXAhcDXS3l+yohR3RawXUQaga9gr4ESLlS7w9t+HbYCb5zvHwCfKuHpKaNDtTu87TFgMnAIcCCwQkTeYYzR3vLBobot3vbT0F6aExYdfl5eejy/Bfi2MWZf5/NOY8xPR3IwY4cR9ojIO7JWHYB921EsvwdOBt5yMqqngMOw3cOfHGbfnmHWK+MD1W4WInIG8G/A6VrACzWqXX+WASeV6FhKaVHdptkDeDvwJxF5DRvu449OZUkJH6pdD8aYDcaYhLEx4W5w0lPCiWo3k3XAXcbyB2zvOZ2kLXyobrMQkRh23o7bx3IcpXrRRs3K8RDwKRFpBhCRXcUGYP4tcIKINIhIC/CxYY7zPeBqEWlwjnMk9s3HrSOw5ffARaQdzJPAAmC9MWY78LhjU6PY4L4nOsuyGantSnUy4bUrIsdgY7sd7745VKoC1a7Inp6/c4GXRmCzEgwTWrfGmOeMMdONMbsbY3bHVrT3N8asH4HdSjBMaO06ts70/D0RG/ZDCT8TXrvA3cCHHLv/CagFNo/AbqXyqG4tRwIvGWPWjcBeZRyhw88rhDHmYRF5F/CkiAB0Y+Py/VFEbsfOCLYR21W7ED8C2oHnRCQBrAfmGmP6RmDOE9gA/E86tr0lIlGsM8Kx6WbgD872NxpjnnW6vHvPaUS2i8iJjv3TgPtEZI0x5ugR2K0EgGoXgB8DdcAjzjV4yhijM0iHHNUuAN8Rkb2wPS5eR2c+Dz2qW6VaUe0C8F0R2Rc7/Pw14NwR2KwEhGoXsDFgbxKR54FBYKGOTAo3qtsUp6JDzyc0or4qXIjIZUC3Meb7QduiKCNBtatUK6pdpRpR3SrVimpXqVZUu0o1orpVxjs6/FxRFEVRFEVRFEVRFEVRlKpCe2qGFBG5Bhtc18sPjTE/K3L/o4Ersha/aow5sRT2DZP2mGxXqhvVrlKtqHaVakR1q1Qrql2lWlHtKtWI6lYZr2ijpqIoiqIoiqIoiqIoiqIoVYUOP1cURVEURVEURVEURVEUparQRk1FURRFURRFURRFURRFUaoKbdRUFEVRFEVRFEVRFEVRFKWq0EZNRVEURVEURVEURVEURVGqCm3UVBRFURRFURRFURRFURSlqvj/xCeClLhwjh8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1329.25x1260 with 56 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data=df_train[cols],diag_kind='hist',hue='IsGoodNews',diag_kws = {'alpha':0.55, 'bins':5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = df_train[cols]\n",
    "data = pd.melt(data,id_vars=\"IsGoodNews\",\n",
    "                    var_name=\"features\",\n",
    "                    value_name='value')\n",
    "plt.figure(figsize=(15,10))\n",
    "sns.swarmplot(x=\"features\", y=\"value\", hue=\"IsGoodNews\", data=data)\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly I saw all the features then came to conclusion many of the features don't really show a good separation,\n",
    "I also saw some kde plots and also some scatter plots and still not much luck"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,X_valid,y_train,y_valid = train_test_split(df_train.drop('IsGoodNews',axis=1),df_train['IsGoodNews'],\n",
    "                                                   test_size=0.30,random_state=22,stratify=df_train['IsGoodNews'],shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          0\n",
      "0  0.924528\n",
      "1  0.934579\n",
      "2  0.901961\n",
      "3  0.878505\n",
      "4  0.877551\n",
      "0.9034248437516428\n"
     ]
    }
   ],
   "source": [
    "cv = KFold(n_splits=5,random_state=22,shuffle=True)\n",
    "# results = pd.DataFrame(columns='training_score', 'test_score')\n",
    "score_avg = []\n",
    "for (train, test), i in zip(cv.split(X_train, y_train), range(5)):\n",
    "    m = lgb.LGBMClassifier(random_state=22,n_estimators=100)\n",
    "    m.fit(X_train.iloc[train],  y_train.iloc[train])\n",
    "    score_avg.append(f1_score(y_pred=m.predict(X_train.iloc[test]),y_true=y_train.iloc[test]))\n",
    "print(pd.DataFrame(data=score_avg))\n",
    "print(sum(score_avg)/len(score_avg))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I manually tuned the hyperparmeters and got the final score."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You just had to trust your local cv in this competition , since the dataset was small i created features but they really didnt help me.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I also tried unormalising the dataset, tho its a hell lot of work to do you can try and get approximate values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_final_preds = m.predict(df_test)\n",
    "df_sub['IsGoodNews']= y_final_preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_sub.to_excel('first_sub_1.xlsx',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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